| In Press |
 | Barrett, H.C., Todd, P.M., Miller, G.F., and Blythe, P.W. (in press). Accurate judgments of intention from motion cues alone. Evolution and Human Behavior.
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| | | Todd, P.M., Rieskamp, J., and Gigerenzer, G. (in press). Social heuristics. In V. Smith and C. Plott (Eds.), Handbook of Experimental Economics Results.
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| | | Gigerenzer, G., and Todd, P.M. (in press). Rationality the fast and frugal way: Introduction. In V. Smith and C. Plott (Eds.), Handbook of Experimental Economics Results.
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| | | Todd, P.M., and Miranda, E. (in press). Putting some (artificial) life into models of musical creativity. In I. Deliege and G. Wiggins (Eds.), Musical creativity: Current research in theory and practise. Psychology Press.
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| | | Fasolo, B., McClelland, G.H., and Todd, P.M. (in press). Escaping the tyranny of choice: When fewer attributes make choice easier. Marketing Theory.
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| | | Mata, R., Wilke, A., and Todd, P.M. (accepted). Adding the missing link back into mate choice research. Commentary on D. Schmitt, Sociosexuality from Argentina to Zimbabwe: A 48-nation study of sex, culture, and strategies of human mating. Behavioral and Brain Sciences.
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| | | Todd, P.M. (in press). How much information do we need? European Journal of Operational Research.
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| | | Rieskamp, J., and Todd, P.M. (in press). The evolution of cooperative strategies for asymmetric social interactions. Theory and Decision.
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| | | Rieskamp, J., Hertwig, R., and Todd, P.M. (in press). Bounded rationality: Two distinct interpretations from psychology. In M. Altman (Ed.), Foundations and extensions of behavioral economics: A handbook. M.E. Sharpe Publishers.
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| | | Todd, P.M., and Heuvelink, A. (in press). Shaping social environments with simple recognition heuristics. In P. Carruthers (Ed.), The innate mind: Culture and cognition.
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| | | Todd, P.M., and Schooler, L.J. (in press). From disintegrated architectures of cognition to an integrated heuristic toolbox. In W. Gray (Ed.), Integrated models of cognitive systems. New York: Oxford University Press.
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| | In Print |
| | Bullock, S., Davis, J.N., and Todd, P.M. (1999). Simplicity rules the roost: Exploring birdbrain parental investment heuristics. In D. Floreano, J.-D. Nicoud, and F. Mondada (Eds.), Advances in Artificial Life (5th European conference, ECAL’99) (Lecture notes in artificial intelligence 1674) (pp. 535-544). Berlin: Springer-Verlag.
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| | | Noble, J., Tuci, E., and Todd, P.M. (1999). An evolutionary simulation model of social learning about food by Norway rats. In D. Floreano, J.-D. Nicoud, and F. Mondada (Eds.), Advances in Artificial Life (5th European conference, ECAL’99) (Lecture notes in artificial intelligence 1674) (pp. 514-523). Berlin: Springer-Verlag.
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| | | Noble, J., and Todd, P.M. (1999). Is it really imitation? A review of simple mechanisms in social information gathering. In K. Dautenhahn and C. Nehaniv (Eds.), Proceedings of the AISB’99 Symposium on Imitation in Animals and Artifacts. Sussex, UK: Society for the Study of Artificial Intelligence and Simulation of Behavior.
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| | | Tuci, E., Noble, J., and Todd, P.M. (1999). “I’ll have what she's having”: A simulation analysis of the copying of food preferences in Norway rats. In K. Dautenhahn and C. Nehaniv (Eds.), Proceedings of the AISB’99 Symposium on Imitation in Animals and Artifacts. Sussex, UK: Society for the Study of Artificial Intelligence and Simulation of Behavior.
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| | | Todd, P.M. (1999). Evolving musical diversity. In Proceedings of the AISB’99 Symposium on Creative Evolutionary Systems (pp. 40-48). Sussex, UK: Society for the Study of Artificial Intelligence and Simulation of Behavior.
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| | | Todd, P.M., and Dieckmann, A. (2005). Heuristics for ordering cue search in decision making. In L.K. Saul, Y. Weiss, and L. Bottou (Eds.), Advances in neural information processing systems 17 (pp. 1393-1400). Cambridge, MA: MIT Press.
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| | | Todd, P.M., Hertwig, R., and Hoffrage, U. (2005). The evolutionary psychology of cognition. In D.M. Buss (Ed.), The handbook of evolutionary psychology (pp. 776-802). Hoboken, NJ: Wiley.
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| | | Todd, P.M., Billari, F.C., and Simão, J. (2005). Aggregate age-at-marriage patterns from individual mate-search heuristics. Demography, 42(3), 559-574.
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| | | Dieckmann, A., and Todd, P.M. (2004). Simple ways to construct search orders. In K. Forbus, D. Gentner, and T. Regier (Eds.), Proceedings of the 26th Annual Conference of the Cognitive Science Society (pp. 309-314). Mahwah, NJ: Lawrence Erlbaum Associates.
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| | | Marsh, B., Todd, P.M., and Gigerenzer, G. (2004). Cognitive heuristics: Reasoning the fast and frugal way. In J.P. Leighton and R.J. Sternberg (Eds.), The nature of reasoning (pp. 273-287). Cambridge, UK: Cambridge University Press.
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| | | Miranda, E., Kirby, S., and Todd, P.M. (2003). On computational models of the evolution of music: From the origins of musical taste to the emergence of grammars. Contemporary Music Review, 22, 91-111.
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| | | van den Broek, E., and Todd, P.M. (2003). Piep piep piep, Ich hab’ dich lieb: Rhythm as an indicator of mate quality. In W. Banzhaf, T. Christaller, P. Dittrich, J.T. Kim, and J. Ziegler (Eds.), Advances in Artificial Life: 7th European Conference Proceedings (ECAL 2003), pp. 425-433. Berlin : Springer-Verlag.
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| | | Hertwig, R., and Todd, P.M. (2003). More is not always better: The benefits of cognitive limits. In D. Hardman and L. Macchi (Eds.),Thinking: Psychological perspectives on reasoning, judgment and decision making (pp. 213-231). Chichester, UK: Wiley.
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| | | Simão, J., and Todd, P.M. (2003). Emergent patterns of mate choice in human populations. Artificial Life, 9, 403-417.
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| | | Todd, P.M., and Gigerenzer, G. (2003). Bounding rationality to the world. Journal of Economic Psychology, 24, 143-165.
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| | | Liu, Y., Gigerenzer, G., and Todd, P.M. (2003). Fast and frugal heuristics simple decision rules based on bounded rationality and ecological rationality. Chinese Journal of Psychological Science, 26, 56-59.
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| | | Todd, P.M., and Billari, F.C. (2003). Population-wide marriage patterns produced by individual mate-search heuristics. In F.C. Billari and A. Prskawetz (Eds.), Agent-based computational demography (pp. 117-137). Berlin: Springer Verlag.
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| | | Dudey, T., and Todd, P.M. (2002). Making good decisions with minimal information: Simultaneous and sequential choice. Journal of Bioeconomics, 3, 195-215.
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| | | Simão, J., and Todd, P.M. (2002). Modeling mate choice in monogamous mating systems with courtship. Adaptive Behavior, 10(2), 113-136.
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| | | Hertwig, R., and Todd, P.M. (2002). Heuristics. Encyclopedia of the Human Brain (vol. 2, pp. 449-460). New York: Academic Press.
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| | | Noble, J., and Todd, P.M. (2002). Imitation or something simpler? Modeling simple mechanisms for social information processing. In K. Dautenhahn and C.L. Nehaniv (Eds.), Imitation in animals and artifacts (pp. 423-439). Cambridge, MA: MIT Press.
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| No abstract.
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| | | Simão, J., and Todd, P.M. (2002). The self-organizing nature of mating systems. In Proceedings of the Workshop on Self-organizing Social Systems.
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| | | Todd, P.M., and Goodie, A.S. (2002). Testing the ecological rationality of base rate neglect. In B. Hallam, D. Floreano, J. Hallam, G. Hayes, and J.-A. Meyer (Eds.), From animals to animats 7: Proceedings of the Seventh International Conference on Simulation of Adaptive Behavior (pp. 215-223). Cambridge, MA: MIT Press/Bradford Books.
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| | | Tuci, E., Harvey, I., and Todd, P.M. (2002). Using a net to catch a mate: Evolving CTRNNs for the dowry problem. In B. Hallam, D. Floreano, J. Hallam, G. Hayes, and J.-A. Meyer (Eds.), From animals to animats 7: Proceedings of the Seventh International Conference on Simulation of Adaptive Behavior (pp. 292-302). Cambridge, MA: MIT Press/Bradford Books.
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| | | Todd, P.M. (2002). Putting some (artificial) life into models of musical creativity. In Musical creativity: Proceedings of the 10th Meeting of the European Society of Cognitive Sciences of Music (ESCOM), Liège, Belgium (CD-ROM).
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| | | Bilotta, E., Miranda, E.R., Pantano, P., and Todd, P.M. (2002). Artificial life models for musical applications: Workshop report. Artificial Life, 8(1), 83-86.
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| | | Todd, P.M., and Gigerenzer, G. (2001). Shepard's mirrors or Simon's scissors? Commentary on R.N. Shepard, Perceptual-cognitive universals as reflections of the world. Behavioral and Brain Sciences, 24(4), 704-705.
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| | | Ketelaar, T., and Todd, P.M. (2001). Framing our thoughts: Ecological rationality as evolutionary psychology's answer to the frame problem. In H.R. Holcomb III (Ed.), Conceptual challenges in evolutionary psychology: Innovative research strategies (pp. 179-211). Norwell, MA: Kluwer Academic Publishers.
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| | | Todd, P.M., and Gigerenzer, G. (2001). Putting naturalistic decision making into the adaptive toolbox. (Comment on Lipshitz et al., "Taking stock of naturalistic decision making”.) Journal of Behavioral Decision Making, 14(5), 381-383.
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| | | Hertwig, R., and Todd, P.M. (2000). Biases to the left, fallacies to the right: Stuck in the middle with null hypothesis significance testing. Commentary on J. Krueger on social bias. PSYCOLOQUY 11(28).
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| | | Todd, P.M., and Kirby, S. (2001). I like what I know: How recognition-based decisions can structure the environment. In J. Kelemen and P. Sosìk (Eds.), Advances in Artificial Life: 6th European Conference Proceedings (ECAL 2001), pp. 166-175. Berlin: Springer-Verlag.
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| | | Simão, J., and Todd, P.M. (2001). A model of human mate choice with courtship that predicts population patterns. In J. Kelemen and P. Sosìk (Eds.), Advances in Artificial Life: 6th European Conference Proceedings (ECAL 2001), pp. 377-380. Berlin: Springer-Verlag.
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| | | Todd, P.M. (2001). Fast and frugal heuristics for environmentally bounded minds. In G. Gigerenzer and R. Selten (Eds.), Bounded rationality: The adaptive toolbox (Dahlem Workshop Report), pp. 51-70. Cambridge, MA: MIT Press.
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| | | Sadrieh, A., Güth, W., Hammerstein, P., Harnad, S., Hoffrage, U., Kuon, B., Munier, B.R., Todd, P.M., Warglien, M., and Weber, M. (2001). Group report: Is there evidence for an adaptive toolbox? In G. Gigerenzer and R. Selten (Eds.), Bounded rationality: The adaptive toolbox (Dahlem Workshop Report), pp. 83-102. Cambridge, MA: MIT Press.
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More information
| | | Noble, J., and Todd, P.M., Tuci, E. (2001). Explaining social learning of food preferences without aversions: An evolutionary simulation model of Norway rats. Proceedings of the Royal Society of London B: Biological Sciences, 268(1463), 141-149.
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| | | Todd, P.M. (2001). Heuristics for decision and choice. In N.J. Smelser and P.B. Baltes (Eds.), International Encyclopedia of the Social & Behavioral Sciences, vol. 10, pp. 6676-6679. Amsterdam: Elsevier.
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| | | Todd, P.M., and Gigerenzer, G. (2000). Simple heuristics that make us smart. Behavioral and Brain Sciences, 23(5), 727-741.
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| | | Todd, P.M., Gigerenzer, G., and the ABC Research Group (2000). How can we open up the adaptive toolbox? (Reply to commentaries.) Behavioral and Brain Sciences, 23(5), 767-780.
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| | | Todd, P.M., Fiddick, L., and Krauss, S. (2000). Ecological rationality and its contents. Thinking and Reasoning, 6(4), 375-384.
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| | | Todd, P.M. (2000). The ecological rationality of mechanisms evolved to make up minds. American Behavioral Scientist, 43(6), 940-956.
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| | | Todd, P.M. (1999). Simple inference heuristics versus complex decision machines. Minds and Machines, 9(4), 461-477.
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| | | Bullock, S., and Todd, P.M. (1999). Made to measure: Ecological rationality in structured environments. Minds and Machines, 9(4), 497-541.
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| | | Davis, J.N., Todd, P.M., and Bullock, S. (1999). Environment quality predicts parental provisioning decisions. Proceedings of the Royal Society of London B, 266, 1791-1797.
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| | | Gigerenzer, G., and Todd, P.M. (1999). Fast and frugal heuristics: The adaptive toolbox. In G. Gigerenzer, P.M. Todd, and the ABC Research Group, Simple heuristics that make us smart. New York: Oxford University Press.
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| | | Berretty, P.M., Todd, P.M., and Martignon, L. (1999). Using few cues to choose: Fast and frugal categorization. In G. Gigerenzer, P.M. Todd, and the ABC Research Group, Simple heuristics that make us smart. New York: Oxford University Press.
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| | | Blythe, P.W., Todd, P.M., and Miller, G.F. (1999). Judging intention from motion: Basic mechanisms for social rationality. In G. Gigerenzer, P.M. Todd, and the ABC Research Group, Simple heuristics that make us smart. New York: Oxford University Press.
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| | | Todd, P.M., and Miller, G.F. (1999). From pride and prejudice to persuasion: Realistic heuristics for mate search. In G. Gigerenzer, P.M. Todd, and the ABC Research Group, Simple heuristics that make us smart. New York: Oxford University Press.
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| | | Davis, J.N., and Todd, P.M. (1999). Simple decision rules for parental investment. In G. Gigerenzer, P.M. Todd, and the ABC Research Group, Simple heuristics that make us smart. New York: Oxford University Press.
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| | | Todd, P.M., and Gigerenzer, G. (1999). What we have learned (so far). In G. Gigerenzer, P.M. Todd, and the ABC Research Group, Simple heuristics that make us smart. New York: Oxford University Press.
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| | | Todd, P.M. (1999). Simulating the evolution of musical behavior. In N. Wallin (Ed.), The origins of music. Cambridge, MA: MIT Press.
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| Abstract:
Prehistoric musical behavior did not fossilize very well, and there are relatively few species alive today with which we can take a comparative approach to the origins of human musical ability. Evolutionary computer simulations provide another means of exploring this question: By constructing a population of artificial music-producers whose behavior can be selected by various fitness-determining critics, we can study hypothetical scenarios for the evolution of musical behavior. To date, most simulations of this type have been constructed for the purpose of creating new forms of computerized music composition systems, rather than to answer scientific questions. But we can survey these systems and the simulation techniques they use to learn about the effects of different types of knowledge representations in the music creators and music critics on the evolutionary process. In addition, we present here the results of a simulation explicitly designed to explore the question of the evolutionary impact of various forms of selection, focusing on sexual selection via coevolving male song-producers and female song-critics. In our model, coevolving creators and critics can increase the diversity of musical behaviors seen both across generations and within any one population. We conclude by indicating further questions that this kind of simulation approach to the evolution of musical behavior can answer.
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| | | Todd, P.M., and Werner, G.M. (1999). Frankensteinian approaches to evolutionary music composition. In N. Griffith and P.M. Todd (Eds.), Musical networks: Parallel distributed perception and performance. Cambridge, MA: MIT Press/Bradford Books.
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| Abstract:
Victor Frankenstein sought to create an intelligent being imbued with the rules of civilized human conduct, who could further learn how to behave and possibly even evolve through successive generations into a more perfect form. Modern human composers similarly strive to create intelligent algorithmic music composition systems that can follow prespecified rules, learn appropriate patterns from a collection of melodies, or evolve to produce output more perfectly matched to some aesthetic criteria. Here we review recent efforts aimed at each of these three types of algorithmic composition. We focus particularly on evolutionary methods, and indicate how monstrous many of the results have been. We present a new method that uses coevolution to create linked artificial music critics and music composers, and describe how this method can attach the separate parts of rules, learning, and evolution together into one coherent body.
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| | | Miller, G.F., and Todd, P.M. (1998). Mate choice turns cognitive. Trends in Cognitive Sciences, 2, 190-198.
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| Abstract:
Evolutionary psychology has revolutionized research on human mate choice and sexual attraction in recent years, combining a rigorous Darwinian framework based on sexual selection theory with a loosely cognitivist orientation to task analysis and mechanism-modelling. This hard-Darwinian, soft-computational approach has been most successful at revealing the adaptive logic behind physical beauty, demonstrating that many sexual cues computed from face and body shape are not arbitrary, but function as reliable indicators of phenotypic and genetic quality. The same approach could be extended from physical to psychological cues if evolutionary psychology built stronger ties with personality psychology, psychometrics, and behavior genetics. A major challenge for mate choice research is to develop more explicit computational models at three levels, specifying (1) the perceptual adaptations that register sexual cues given sensory input, (2) the judgment adaptations that integrate multiple cues into assessments of overall attractiveness, and (3) the search strategies that people follow in trying to form mutually attracted pairs. We describe recent efforts and possible extensions in these directions. The resulting confluence between evolutionary principles, cognitive models, and game-theoretic insights can put mate choice research at the vanguard of an emerging "evolutionary cognitive science" more concerned with domain-specific mental adaptations than with domain-general intelligence.
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| | | Todd, P.M., and Lopez, A. (1998). Pulling the trigger on the living kind module. Commentary on S. Atran, Folk biology and the anthropology of science: Cognitive universals and cultural particulars. Behavioral and Brain Sciences, 21(4):592.
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| Abstract:
Atran speculates that a triggering algorithm for a living kind module could involve inputs from other modules that detect animacy and intentionality. Here we further speculate how algorithms for detecting specific intentions could be used to trigger between- or within-species categorization. We further indicate why such categorization may be adaptively important in Eldredge's energy and information realms.
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| | | Todd, P.M., and Borges, B. (1997). Designing socially intelligent agents for the ultimatum game. In K. Dautenhahn (Ed.), Socially intelligent agents-Papers from the 1997 Fall Symposium (Technical Report FS-97-02) (pp. 134-136). Menlo Park, CA: AAAI Press.
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| Abstract:
To build socially intelligent artificial agents, we must decide how much-and what kind of-intelligence to endow them with. Vriend (1997) has recently questioned whether adding reasoning will help or hinder the behavior of simple learning agents in social games. We show that adding the right kind of reasoning will help agents act more intelligently by learning more quickly.
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| | | Berretty, P.M., Todd, P.M., and Blythe, P.W. (1997). Categorization by Elimination: A fast and frugal approach to categorization. In M.G. Shafto and P. Langley (Eds.), Proceedings of the Nineteenth Annual Conference of the Cognitive Science Society (pp. 43-48). Mahwah, NJ: Lawrence Erlbaum Associates.
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| Abstract:
People and other animals are very adept at categorizing stimuli even when many features cannot be perceived. Many psychological models of categorization, on the other hand, assume that an entire set of features is known. We present a new model of categorization, called Categorization by Elimination, that uses as few features as possible to make an accurate category assignment. This algorithm demonstrates that it is possible to have a categorization process that is fast and frugal-using fewer features than other categorization methods--yet still highly accurate in its judgments. We show that Categorization by Elimination does as well as human subjects on a multi-feature categorization task, judging intention from animate motion, and that it does as well as other categorization algorithms on data sets from machine learning. Specific predictions of the Categorization by Elimination algorithm, such as the order of cue use during categorization and the time-course of these decisions, still need to be tested against human performance.
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| | | Werner, G.M., and Todd, P.M. (1997). Too many love songs: Sexual selection and the evolution of communication. In P. Husbands and I. Harvey (Eds.), Fourth European Conference on Artificial Life(pp. 434-443). Cambridge, MA: MIT Press/Bradford Books.
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| Abstract:
Communication signals in many animal species (including humans) show a surprising amount of variety both across time and at any one instant in a population. Traditional accounts and simulation models of the evolution of communication offer little explanation of this diversity. Sexual selection of signals used to attract mates, and the coevolving preferences used to judge those signals, can instead provide a convincing mechanism. Here we demonstrate that a wide variety of ``songs'' can evolve when male organisms sing their songs to females who judge each male's output and decide whether or not to mate with him based on their own coevolved aesthetics. Evolved variety and rate of innovation are greatest when females combine inherited song preferences with a desire to be surprised. If females choose mates from a small pool of candidates, diversity and rate of change are also increased. Such diversity of communication signals may have implications for the evolution of brains as well.
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| | | Todd, P.M., and Miller, G.F. (1997a). How cognition shapes cognitive evolution. IEEE Expert, July/August, 7-9.
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| | | Todd, P.M., and Miller, G.F. (1997b). Biodiversity through sexual selection. In C.G. Langton and K. Shimohara (Eds.), Artificial life V: Proceedings of the Fifth International Workshop on the Synthesis and Simulation of Living Systems (pp. 289-299). Cambridge, MA: MIT Press/Bradford Books.
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| Abstract:
What engenders biodiversity? Natural selection certainly adapts species to their ecological niches, but does it really create all of the new niches and new species to fill them? Consider: the most successful, complex, and numerous species on earth are composed of sexually-reproducing animals and flowering plants. Both groups typically undergo a form of sexual selection through mate choice: animals are selected by conspecifics and flowering plants are selected by heterospecific pollinators. This common feature suggests that the evolution of biodiversity may be driven not simply by natural-selective adaptation to ecological niches, but by subtle interactions between natural selection and sexual selection. This paper presents theoretical arguments and simulation results in support of our view that sexual selection creates new fitness peaks (and thus new niches), helps species escape from old local optima to find new, better peaks, and promotes speciation to increase the number of lineages searching for peaks. Natural selection is a precondition for biodiversity (because it permits ecological adaptation), but sexual selection may often be a more direct cause of species diversity for animals and flowering plants. The paper concludes with implications for evolutionary engineering, human evolution, and conservation priorities.
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| | | Todd, P.M. (1997). Searching for the next best mate. In R. Conte, R. Hegselmann, and P. Terna (Eds.), Simulating social phenomena (pp. 419-436). Berlin: Springer-Verlag.
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| Abstract:
How do we humans go about choosing a mate? Do we shop for them, checking prices and values and selecting the best? Do we apply for them, wooing several and taking the best that accepts us in return? Or do we screen them, testing one after another in succession until the right one comes along? Economists and other behavioral scientists have analyzed these mate-choice approaches to find their optimal algorithmic solutions; but what people really do is often quite different from these optima. In this paper, we analyze the third approach of mate choice as applicant screening and show through simulation analyses that a traditional optimal solution to this problem--the 37% rule--can be beaten along several dimensions by a class of simple ``satisficing'' algorithms we call the Take the Next Best mate choice rules. Thus, human mate search behavior should not necessarily be compared to the lofty optimal ideal, but instead may be more usefully studied through the development and analysis of possible ``fast and frugal'' mental mechanisms.
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| | | Todd, P.M., and Yanco, H.A. (1996). Environmental effects on minimal behaviors in the minimat world. Adaptive Behavior, 4(3-4), 365-413.
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| Abstract:
The structure of an environment affects the behaviors of the organisms that have evolved in it. How is that structure to be described, and how can its behavioral consequences be explained and predicted? We aim to establish initial answers to these questions by simulating the evolution of very simple organisms in simple environments with different structures. Our artificial creatures, called "minimats," have neither sensors nor memory and behave solely by picking amongst the actions of moving, eating, reproducing, and sitting, according to an inherited probability distribution. Our simulated environments contain only food (and multiple minimats) and are structured in terms of their spatial and temporal food density and the patchiness with which the food appears. Changes in these environmental parameters affect the evolved behaviors of minimats in different ways, and all three parameters are of importance in describing the minimat world. One of the most useful behavioral strategies that evolves is "looping" movement, which allows minimats--despite their lack of internal state--to match their behavior to the temporal (and spatial) structure of their environment. Ultimately we find that minimats construct their own environments through their individual behaviors, making the study of the impact of global environment structure on individual behavior much more complex.
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| | | Blythe, P.W., Miller, G.F., and Todd, P.M. (1996). Human simulation of adaptive behavior: Interactive studies of pursuit, evasion, courtship, fighting, and play. In P. Maes, M.J. Mataric, J.-A. Meyer, J. Pollack, and S.W. Wilson (Eds.), From animals to animats 4: Proceedings of the Fourth International Conference on Simulation of Adaptive Behavior (pp. 13-22). Cambridge, MA: MIT Press/Bradford Books.
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| Abstract:
To understand more about how animate motion is generated and perceived, we need quantitative analyses of motion trajectories from organisms interacting in various important adaptive tasks. Such data is difficult to obtain for most animals, but one species provides a ready source. We have developed software that allows human subjects to generate such motion data by interacting across a computer network in on-screen pursuit and evasion, fighting, courtship, and play. Each subject uses a mouse to control a "bug" that moves in a 2-D environment with another bug controlled by a second remote subject. We have visualized and analyzed the resulting motion data for each task in several ways: 3-D space-time plots of the trajectories themselves, scatterplots of one bug's positions relative to the other, and statistical measures of trajectory parameters including velocity, vorticity, and energy. All of these methods distinguish between the different motion categories. Having human subjects perform these kinds of scenarios can lead to better techniques for analyzing, comparing, and designing the motion capacities of simulated agents.
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| | | Blumberg, B.M., Todd, P.M., and Maes, P. (1996). No bad dogs: Ethological lessons for learning in Hamsterdam. In P. Maes, M.J. Mataric, J.-A. Meyer, J. Pollack, and S.W. Wilson (Eds.), From animals to animats 4: Proceedings of the Fourth International Conference on Simulation of Adaptive Behavior (pp. 295-304). Cambridge, MA: MIT Press/Bradford Books.
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| Abstract:
We present an architecture for autonomous creatures that allows learning to be combined with action selection, based on ideas from ethology. We show how temporal-difference learning may be used within the context of an ethologically inspired animat architecture to build and modify portions of the behavior network, and to set fundamental parameters including the strength associated with individual Releasing Mechanisms, the time course associated with appetitive behaviors, and the learning rates to be used based on the observed reliability of specific contingencies. The learning algorithm has been implemented as part of the Hamsterdam toolkit for building autonomous animated creatures. When implemented in Silas, a virtual dog, the algorithm enables Silas to be trained using classical and instrumental conditioning.
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| | | Todd, P.M. (1996). Sexual selection and the evolution of learning. In R. Belew and M. Mitchell (Eds.), Adaptive individuals in evolving populations: Models and algorithms (pp. 365-393). Reading, MA: Addison-Wesley.
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| Abstract:
There are two realms in which every living organism must operate. The first is an economic realm of matter and energy, requiring the accrual of resources necessary for an organism's ongoing survival. The second is a genealogical realm of genetic information, requiring appropriate action to ensure an organism's ongoing genetic perpetuation. As Eldredge (1986, p. 351) puts it, "organisms seem to be both energy conversion machines and reproducing `packages' of genetic information." Evolution, as "the primary channel of communication between living systems and their environments" (Plotkin & Odling-Smee, 1979, p. 13), clearly shapes organisms in response to both of these environmental realms. Less well appreciated is the fact that learning, as a secondary means of adapting an organism's internal organization to the external order in the environment, can similarly operate in both domains. In this paper, we will first consider the ways in which learning can evolve through sexual selection, including the sexually selected functions learning may have, the time scales at which these kinds of learning operate, and the differences from naturally selected evolution of learning. We will present a simulation model of the evolution of one particular form of sexually selected learning--parental imprinting--to illustrate these points. We then investigate how learning can affect sexual selection and evolution in turn, leading to such macroevolutionary effects as speciation and runaway selection. This is again illustrated through the simulation study of parental imprinting. Finally, we draw conclusions from this line of inquiry, and describe further directions for the study of sexually selected learning.
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| | | Todd, P.M. (1996). The causes and effects of evolutionary simulation in the behavioral sciences. In R. Belew and M. Mitchell (Eds.), Adaptive individuals in evolving populations: Models and algorithms (pp. 211-224). Reading, MA: Addison-Wesley.
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| Abstract:
Things change. To prolong their existence in the face of this constant flux (and thereby increase their possibilities for reproduction), organisms must change, too. The behavioral sciences have focused on the ways in which the behavior of organisms changes over time at a variety of scales: momentary decision making, learning, development, and cultural change. However, these four adaptive processes do not capture the entire story. To fully appreciate the behavior of organisms in their environment, we must take into account the evolution of their behavior as well. The behavioral sciences (primarily here psychology, but also linguistics, anthropology, and sociology) are largely only now beginning to do so in earnest. In this chapter, we will briefly explore why evolutionary adaptation has often been left out of the behavioral/cognitive picture, and what is causing it to be painted (back) in now. There is much that remains to be done in this endeavor, and we will discuss the effects this ongoing research will have on the continuing evolution of the behavioral sciences themselves.
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| | | Miller, G.F., and Todd, P.M. (1995). The role of mate choice in biocomputation: Sexual selection as a process of search, optimization, and diversification. In W. Banzhaf and F.H. Eeckman (Eds.), Evolution and biocomputation: Computational models of evolution (pp. 169-204). Berlin: Springer-Verlag.
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| Abstract:
The most successful, complex, and numerous species on earth are composed of sexually-reproducing animals and flowering plants. Both groups typically undergo a form of sexual selection through mate choice: animals are selected by conspecifics and flowering plants are selected by heterospecific pollinators. This suggests that the evolution of phenotypic complexity and diversity may be driven not simply by natural-selective adaptation to econiches, but by subtle interactions between natural selection and sexual selection. This paper reviews several theoretical arguments and simulation results in support of this view. Biological interest in sexual selection has exploded in the last 15 years (see Andersson & Bradbury, 1987; Cronin, 1991), but has not yet been integrated with the biocomputational perspective on evolution as a process of search and optimization (Holland, 1975; Goldberg, 1989). In the terminology of sexual selection theory, mate preferences for "viability indicators" (e.g. Hamilton & Zuk, 1982) may enhance evolutionary optimization, and mate preferences for "arbitrary traits" (e.g. Fisher, 1930) may enhance evolutionary search and diversification. Specifically, as a short-term optimization process, sexual selection can: (1) speed evolution by increasing the accuracy of the mapping from phenotype to fitness and thereby decreasing the "noise" or "sampling error" characteristic of many forms of natural selection, and (2) speed evolution by increasing the effective reproductive variance in a population even when survival-relevant differences are minimal, thereby imposing an automatic, emergent form of "fitness scaling", as used in genetic algorithm optimization methods (see Goldberg, 1989). As a longer-term search process, sexual selection can: (3) help populations escape from local ecological optima, essentially by replacing genetic drift in Wright's (1932) "shifting balance" model with a much more powerful and directional stochastic process, and (4) facilitate the emergence of complex innovations, some of which may eventually show some ecological utility. Finally, as a process of diversification, sexual selection can (5) promote spontaneous sympatric speciation through assortative mating, increasing biodiversity and thereby increasing the number of reproductively isolated lineages performing parallel evolutionary searches (Todd & Miller, 1991) through an adaptive landscape. The net result of these last three effects is that sexual selection may be to macroevolution what genetic mutation is to microevolution: the prime source of potentially adaptive heritable variation, at both the individual and species levels. Thus, if evolution is understood as a biocomputational process of search, optimization, and diversification, sexual selection can play an important role complementary to that of natural selection. In that role, sexual selection may help explain precisely those phenomena that natural selection finds troubling, such as the success of sexually-reproducing lineages, the speed and robustness of evolutionary adaptation, and the origin of otherwise puzzling evolutionary innovations, such as the human brain (Miller, 1993). Implications of this view will be discussed for biology, psychology, and evolutionary approaches to artificial intelligence and robotics.
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| | | Todd, P.M., Wilson, S.W., Somayaji, A.B., and Yanco, H.A. (1994). The blind breeding the blind: Adaptive behavior without looking. In D. Cliff, P. Husbands, J.-A. Meyer, and S.W. Wilson (Eds.), From animals to animats 3: Proceedings of the Third International Conference on Simulation of Adaptive Behavior (pp. 228-237). Cambridge, MA: MIT Press/Bradford Books.
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Sensors and internal states are often considered necessary components of any adaptively behaving organism, providing the information needed to adapt a creature's behavior in response to conditions in its external or internal environment. But adaptive, survival-enhancing behavior is possible even in simple simulated creatures lacking all direct contact with their environment -- evolutionarily shaped blind action may suffice to keep a population of creatures alive and reproducing. In this paper, we consider the evolution of the behavioral repertoires of such sensor-less creatures in response to environments of various types. Different spatial and temporal distributions of food result in the evolution of very different behavioral strategies, including the use of looping movements as time-keepers in these otherwise cognitively-challenged creatures. Exploring the level of adaptiveness available in even such simple creatures as these serves to establish a baseline to which the adaptive behavior of animats with sensors and internal states can be compared.
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| | | Todd, P.M. (1994). Artificial death. In C. Schneider (Ed.), Jahresring 41 (German yearbook for modern art) (pp. 90-107). Munich: Verlag Silke Schreiber. (Also in same volume in German, under the title "Kunstlicher Tod," pp. 233-246.)
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We have developed an open-ended system for studying the evolution of behavior in a population of simulated creatures. The population grows when individual creatures actively reproduce; population size is kept in check by the death of creatures that run out of energy. This allows new creatures, with new behaviors, to have access to the environmental resources they will need to survive, so that constant turnover of individuals and consequent evolution can take place in the population. In many instances, though, super-individuals can evolve that choose to opt out of the energy-depleting reproduction process, becoming for all purposes immortal and thereby stalling the course of evolution. To solve this problem of immortality, new forms of death and senescence, including the possibility of suicide, must be added. Differences in the simple rules used for "reaping functions" can have widely varying effects on the evolved behaviors of individuals and the global behavior of the population as a whole, and carry with them implications for the evolution of death in natural systems.
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| | | Todd, P.M., and Miller, G.F. (1993). Parental guidance suggested: How parental imprinting evolves through sexual selection as an adaptive learning mechanism. Adaptive Behavior, 2(1), 5-47.
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| Abstract:
The study of adaptive behavior, including learning, usually centers on the effects of natural selection for individual survival. But because reproduction is evolutionarily more important than survival, sexual selection through mate choice (Darwin, 1871), can also have profound consequences on the evolution of creatures' bodies and behaviors. This paper shows through simulation models how one type of learning, parental imprinting, can evolve purely through sexual selection, to help in selecting appropriate mates and in tracking changes in the phenotypic makeup of the population across generations. At moderate mutation rates, when population-tracking becomes an important but still soluble problem, imprinting proves more useful and evolves more quickly than at low or high mutation rates. We also show that parental imprinting can facilitate the formation of new species. In reviewing the biological literature on imprinting, we note that these results confirm some previous speculations by other researchers concerning the adaptive functions and evolutionary consequences of imprinting. Finally, we discuss how sexual selection through mate choice may have great scientific implications for our understanding of the interactions between evolution, learning, and behavior, and potentially important engineering applications for increasing the efficiency of evolutionary search and optimization methods.
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| | | Rumelhart, D.E., and Todd, P.M. (1993). Learning and connectionist representations. In D.E. Meyer and S. Kornblum (Eds.), Attention and performance XIV (pp. 3-30). Cambridge, MA: MIT Press/Bradford Books.
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| Abstract:
Connectionist modeling is undergoing a renaissance. As the merits of brain-style computation (Rumelhart, 1990) have become apparent, a bewildering variety of connectionist applications have cropped up throughout the cognitive sciences and engineering (for instance, see Lippmann, Moody, and Touretzky, 1991). One of the central issues in all of these models is the representation of knowledge in the connectionist network. Getting a coherent picture of "what goes on" inside a network as it develops, manipulates, and alters the representation of the knowledge it processes is vital for our understanding of connectionist information processing, and likely for our understanding of the minds these systems model. In this paper we explore the sorts of representations that connectionist systems employ, and the crucial role learning plays in constructing them.
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| | | Todd, P.M., and Wilson, S.W. (1993). Environment structure and adaptive behavior from the ground up. In J.-A. Meyer, H.L. Roitblat, and S.W. Wilson (Eds.), From animals to animats 2: Proceedings of the Second International Conference on Simulation of Adaptive Behavior (pp. 11-20). Cambridge, MA: MIT Press/Bradford Books.
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We describe a framework for exploring the evolution of adaptive behaviors in response to different physical environment structures. We focus here on the evolving behavior-generating mechanisms of individual creatures, and briefly mention some approaches to characterizing different environments in which various behaviors may prove adaptive. The environments are described initially as simple two-dimensional grids containing food arranged in some layout. The creatures in these worlds can have evolved sensors, internal states, and actions and action-triggering conditions. By allowing all three of these components to evolve, rather than prespecifying any of them, we can explore a wide range of behavior types, including "blind" and memoryless behaviors. Our system is simple and well-defined enough to allow complete specification of the range of possible action-types (including moving, eating, and reproducing) and their effects on the energy levels of the creature and the environment (the bioenergetics of the world). Useful and meaningful ways of characterizing the structures of environments in which different behaviors will emerge remain to be developed.
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| | | Miller, G.F., and Todd, P.M. (1993). Evolutionary wanderlust: Sexual selection with directional mate preferences. In J.-A. Meyer, H.L. Roitblat, and S.W. Wilson (Eds.), From animals to animats 2: Proceedings of the Second International Conference on Simulation of Adaptive Behavior (pp. 21-30). Cambridge, MA: MIT Press/Bradford Books.
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| Abstract:
In the pantheon of evolutionary forces, the optimizing Apollonian powers of natural selection are generally assumed to dominate the dark Dionysian dynamics of sexual selection. But this need not be the case, particularly with a class of selective mating mechanisms called "directional mate preferences" (Kirkpatrick, 1987). In previous simulation research, we showed that non-directional assortative mating preferences could cause populations to spontaneously split apart into separate species (Todd & Miller, 1991). In this paper, we show that directional mate preferences can cause populations to wander capriciously through phenotype space, under a strange form of runaway sexual selection, with or without the influence of natural selection pressures. When directional mate preferences are free to evolve, they do not always evolve to point in the direction of natural-selective peaks. Sexual selection can thus take on a life of its own, such that mate preferences within a species become a distinct and important part of the environment to which the species' phenotypes adapt. These results suggest a broader conception of "adaptive behavior," in which attracting potential mates becomes as important as finding food and avoiding predators. We present a framework for simulating a wide range of directional and non-directional mate preferences, and discuss some practical and scientific applications of simulating sexual selection.
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| | | Todd, P.M. (1992). The animat approach to intelligent behavior. Computer, 25(11), 78-81.
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The traditional approach to building artificially intelligent systems can be characterized as a top-down methodology: creating large complex systems with massive amounts of knowledge dedicated to solving one particular aspect of supposedly intelligent behavior, such as theorem-proving, or playing chess, or understanding natural language. At some point, it is hoped, all of these separate modules can be connected together to create a wholly intelligent system, but until then, we have a collection of idiots savants, who may, for instance, be able to beat all but a handful of the humans on this planet at chess, but lack the ability possessed by even the lowliest housefly to navigate through a crowded room to the chessboard. The failure of three decades of AI research to even match the behavioral repertoire of insects, let alone humans, and a heightened awareness that what it takes to act intelligently in a challenging environment has little to do with game-playing and theorem-proving, has led to the emergence of a new approach to creating intelligent systems, one that starts from the bottom: the animat path to AI.
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| | | Todd, P.M. (1992). A connectionist system for exploring melody space. In Proceedings of the 1992 International Computer Music Conference (pp. 65-68). San Francisco: International Computer Music Association.
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Connectionist (neural network) systems allow a new approach to algorithmic music composition. We present here a connectionist system which allows composers to explore regions of "melody space" nearby other melodies of the composer's choosing. The composer selects a set of melodies that will define the melody space, positions them on a 2-d plane with a mouse-based graphic interface, trains a connectionist network to produce those melodies, and listens to the new "interpolated" melodies that the network generates corresponding to intermediate points in the 2-d plane. Future enhancements include using another network to automatically rate the interpolated melodies, allowing the composer to only listen to promising new creations.
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| | | Todd, P.M. (1991). Neural networks for applications in the arts. In M. Scott (Ed.), Proceedings of the Eleventh Annual Symposium on Small Computers in the Arts (pp. 3-8). Philadelphia, PA: Small Computers in the Arts Network, Inc.
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A new approach to computer art applications is provided by the rapidly expanding field of neural networks. Rather than operate in the traditional style of preprogrammed rule-following systems, neural networks have the power to *learn* to produce specific types of outputs from specific inputs, based on examples they are taught. Thus, instead of having to specify *how* to create a certain artwork, the artist can instead teach a network *examples* of the desired output, and have the network generate new instances in that style. We need not specify the steps involved in creating a Rodin sculpture--we can just collect instances of the sorts of sculpture we'd like to get and use those to train a network. This sort of thing is the promise of neural network applications in the arts, stated in a very provocative and exaggerated manner. But we are beginning to realize this promise in limited domains, and the space for further applications and explorations of these techniques is wide open. In this paper, I will briefly describe neural networks, some of what they can and can't do, some of what they have done already in the arts, primarily music, and some of what they can be applied to in other areas.
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| | | Todd, P.M., and Miller, G.F. (1991). On the sympatric origin of species: Mercurial mating in the quicksilver model. In R.K. Belew and L.B. Booker (Eds.), Proceedings of the Fourth International Conference on Genetic Algorithms (pp. 547-554). San Mateo, CA: Morgan Kaufmann.
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Traditional models of how interbreeding populations split apart into reproductively isolated populations (species) require the intervention of geographic barriers to mating or disruptive selection. We develop an alternate Quicksilver Model of speciation, and show through simulation that sympatric (barrier-less) speciation can occur spontaneously, frequently, and robustly even in the absence of external divisive forces given certain broad conditions: (1) individuals have evolvable mate preferences based on degree of similarity to oneself along certain phenotypic dimensions, and (2) individuals compete to match the mate preferences of other individuals, and to have appropriate mate preferences themselves (i.e. sexual selection exists). Our model's success defends the notion of sympatric speciation against charges that it is impossible, implausible, or unlikely. It also offers an new vision of macroevolution based on appreciating the way modest psychological mechanisms of mate choice can have strong emergent effects on macroevolutionary dynamics.
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| | | Todd, P.M., and Miller, G.F. (1991). Exploring adaptive agency III: Simulating the evolution of habituation and sensitization. In H.-P. Schwefel and R. Maenner (Eds.), Proceedings of the First International Conference on Parallel Problem Solving from Nature (pp. 307-313). Berlin: Springer-Verlag.
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Sensitization and habituation, we postulate, both serve the adaptive function of cluster-tracking: entraining and exploiting the basic spatio-temporal regularities in the environment. To better understand the adaptive pressures shaping cluster-tracking, we used a genetic algorithm to evolve simulated creatures controlled by neural networks. The creatures make decisions about when to eat in simple simulated environments containing "food" (which raises fitness) and "poison" (which lowers it) based on sensory cues. Food and poison were distributed in randomly-occurring clusters of a certain scale fixed for each environment. Sensory input had a limited accuracy level fixed for each environment. When sensory accuracy is moderate and food and poison come in fairly large clusters, certain time-delay feedback connections evolve to allow cluster-tracking. We ran several simulations for each of 6 cluster-scales and each of 7 levels of sensory accuracy. As expected, the average number of generations required to evolve cluster-tracking follows a U-shaped curve as a function of sensory accuracy, and generally declines as cluster scale increases. But an asymmetry in this ravine-like surface illuminates some previously unsuspected complexities of sensitization and habituation.
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| | | Miller, G.F., and Todd, P.M. (1991). Let evolution take care of its own. Commentary on C.W. Clark, Modeling behavioral adaptations. Behavioral and Brain Sciences, 14(1), 101-102.
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| | | Todd, P.M., and Miller, G.F. (1991). Exploring adaptive agency II: Simulating the evolution of associative learning. In J.-A. Meyer and S.W. Wilson (Eds.), From animals to animats: Proceedings of the First International Conference on Simulation of Adaptive Behavior (pp. 306-315). Cambridge, MA: MIT Press/Bradford Books.
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We consider psychology as the study of adaptive agency, investigating the processes and mechanisms resulting in fitness-increasing behavior in the world. A central issue in psychology so construed becomes: what are the relations between the primary adaptive process of evolution by natural selection, and the adaptive processes psychologists call "learning"? In particular, under what conditions would learning evolve? To explore this issue, we use genetic algorithms to simulate the evolution by natural selection of neural networks, which in turn control the behavior of simple creatures in virtual environments. We have developed what we consider the simplest possible environmental challenge in which unsupervised associative learning could prove adaptive: "bootstrapping" the learned use of one highly accurate, but individually varying, sensory modality by another less accurate, but evolutionarily stable, modality. We have found a possibly quite general U-shaped curve relating the time (in number of generations) to evolve the use of unsupervised learning on the varying "bootstrapped" modality, to the accuracy of perception in the stable modality which guides this learning. This U-shaped curve appears to represent a trade-off between the adaptive pressure to evolve learning (which peaks when perception accuracy in the stable guiding modality is at chance) and the ease of learning during a given lifespan (which peaks when this accuracy is perfect.)
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| | | Trubitt, D.R., and Todd, P.M. (1991). The computer musician: Neural networks and computer music. Electronic Musician, 7(1), 20-24.
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| | | Miller, G.F., and Todd, P.M. (1990). Exploring adaptive agency I: Theory and methods for simulating the evolution of learning. In D.S. Touretzky, J.L. Elman, T.J. Sejnowski, and G.E. Hinton (Eds.), Proceedings of the 1990 Connectionist Models Summer School (pp. 65-80). San Mateo, CA: Morgan Kaufmann.
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| Abstract:
Psychology construed as the scientific study of adaptive agency can include not only modelling of specific psychological adaptations in particular species, but general exploration of the adaptive processes (including evolution, learning, and computation) that build, modify, and instantiate those adaptations. Connectionist theory has concentrated on understanding the adaptive processes of learning and computation, and has assumed general-purpose learning principles as the prime constructors of psychological adaptations. But connectionism has thereby ignored the central lesson of a century of learning theory in psychology: learning mechanisms must be understood in terms of their specific adaptive functions, just like other psychological adaptations. This paper introduces the notion of psychology as the study of adaptive agency, outlines a hierarchy of adaptive processes underlying adaptive agency, and reviews the history of learning theory and the emergence of ecological and evolutionary approaches to learning. We then develop a taxonomy of adaptive functions that learning mechanisms might serve, and outline a general simulation framework for exploring those adaptive functions. Finally, we present empirical results concerning the simulated evolution of associative learning.
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| | | Todd, P.M. (1989). A connectionist approach to algorithmic composition. Computer Music Journal, 13(4), 27-43.
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With the advent of von Neumann-style computers, widespread exploration of new methods of music composition became possible. The approach to algorithmic composition based on the wedding between von Neumann computing machinery and rule-based software systems has been prevalent for the past thirty years. The arrival of a new paradigm for computing--parallel distributed processing (PDP), or connectionism--has made a new approach to algorithmic composition possible. One of the major features of the PDP approach is that it replaces strict rule-following behavior with regularity-learning and generalization. This fundamental shift allows the development of new algorithmic composition methods which rely on learning the structure of existing musical examples and generalizing from these learned structures to compose new pieces. This paper presents a particular type of PDP network for music composition applications. Various issues are discussed in designing the network, choosing the music representation used, training the network, and using it for composition. Comparisons are made to previous methods of algorithmic composition, and examples of the network's output are presented.
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| | | Bharucha, J.J., and Todd, P.M. (1989). Modeling the perception of tonal structure with neural nets. Computer Music Journal, 13(4), 44-53.
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What can we say about the perception of music by the silent majority, the listeners for whom music is written but who can neither create music nor articulate their musical experience? How do they passively acquire their demonstrably sophisticated intuitions about musical patterns typical of their culture? Experiments in the cognitive psychology of music have cast some light on the first question. Recent developments in neural net learning now enable us to explore answers to the second. In this article, we discuss an aspect of the experience of the nonmusician listener, namely, contextual influences on the perception of pitch. We do not pretend to capture the listener's experience in all its glory. We limit our discussion to tonal implications and expectations and to memory for pitch sequences. We first summarize some psychological research, and then explore how neural networks can be employed to model the acquisition of these phenomena through passive exposure.
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| | | Miller, G.F., Todd, P.M., and Hegde, S.U. (1989). Designing neural networks using genetic algorithms. In J.D. Schaffer (Ed.), Proceedings of the Third International Conference on Genetic Algorithms (pp. 379-384). San Mateo, CA: Morgan Kaufmann.
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We present a genetic algorithm method that evolves neural network architectures for specific tasks. Each network architecture is represented as a connection constraint matrix mapped directly into a bit string genotype. Modified standard genetic operators are used during evolution. Architecture fitness is assessed by training particular network instantiations and recording their final performance error. Three applications of this method to simple network mapping tasks are discussed, and we conclude with an indication of possible extensions to this work.
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| | | Todd, P.M. (1988). A sequential network design for musical applications. In D. Touretzky, G. Hinton, and T. Sejnowski (Eds.), Proceedings of the 1988 Connectionist Models Summer School (pp. 76-84). San Mateo, CA: Morgan Kaufmann.
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A sequential connectionist network of the type first described by Jordan (1986) is presented for applications in the musical domain. Two such applications are described: composition of novel melodies based on learned examples, and modelling of psychological expectation violation in music. The issues involved in selection of pitch and time representations for the network are explored.
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| | Reviews |
| | Todd, P.M. (2004). The new AI meets the machine musician. Review of R. Rowe, Machine musicianship. Musicae Scientiae, VIII(1), 127-131.
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| | | Todd, P.M. (1999). Reason now and then. Review of D. B. Calne, Within reason: Rationality and human behavior. Science, 286(5446), 1861-1862.
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| | | Todd, P.M. (1999). Review of R. Dukas (Ed.), Cognitive ecology. Animal Cognition, 2, 121-122.
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| | | Todd, P.M. (1995). Adaptive radiation of alife memes: Review of eight artificial life book/software packages. Adaptive Behavior, 3(3), 349-354.
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| | | Todd, P.M., and Blumberg, B. (1995). Review of D. McFarland and T. Boesser, Intelligent behavior in animals and robots. Animal Behaviour, 49(2), 562-3.
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| | | Todd, P.M. (1994). Unsettling the centralized mindset. Review of M. Resnick, Turtles, termites, and traffic jams: Explorations in massively parallel microworlds. Adaptive Behavior, 3(2), 225-229.
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| | | Miller, G.F., and Todd, P.M. (1994). A bottom-up approach with a clear view of the top: How human evolutionary psychology can inform adaptive behavior research. Review of J.H. Barkow, L. Cosmides, and J. Tooby (Eds.), The adapted mind: Evolutionary psychology and the generation of culture. Adaptive Behavior, 3(1), 83-95.
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| | | Todd, P.M. (1993). Review of S. Forrest (Ed.), Emergent computation: Self-organizing, collective, and cooperative phenomena in natural and artificial computing networks. Artificial Intelligence, 60, 171-183. Also appears in W.J. Clancey, S.W. Smoliar, and M.J. Stefik (Eds.), Contemplating minds: A forum for artificial intelligence (pp. 349-361). Cambridge, MA: MIT Press (1994).
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| | | Todd, P.M. (1989). Review of T. Kohonen, A self-learning musical grammar, or 'Associative memory of the second kind.' Neural Network Review, 3, 114-116.
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| | Books |
| | Todd, P.M., Gigerenzer, G., and the ABC Research Group (in preparation). Ecological rationality: Intelligence in the world. New York: Oxford University Press.
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| | | Bilotta, E., Miranda, E.R., Pantano, P., and Todd, P.M. (Eds.) (2001). ALMMA 2001: Proceedings of the workshop on artificial life models for musical applications. Cosenza, Italy: Editoriale Bios.
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| | | Gigerenzer, G., Todd, P.M., and the ABC Research Group (1999). Simple heuristics that make us smart. New York: Oxford University Press.
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| | | Griffith, N., and Todd, P.M. (Eds.) (in press). Musical networks: Parallel distributed perception and performance. Cambridge, MA: MIT Press/Bradford Books.
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| | | Todd, P.M., and Loy, D.G. (Eds.) (1991). Music and connectionism. Cambridge, MA: MIT Press.
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