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2003
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Course Description |
Ecological Rationality and
Heuristic Decision Making
Peter M. Todd
Center for Adaptive Behavior and Cognition
Max Planck Institute for Human Behavior
Berlin, Germany
This course presents recent research exploring the ways that simple heuristic mechanisms can make good decisions, despite using little information and little computation, by exploiting the structure of information available in the environment. Heuristics for making simultaneous and sequential choices will be covered in a variety of domains, from comparing city sizes to getting married to finding a parking space, along with the methods for studying and modeling such decision making.
Day 1: Main lecture: Introduction to ecological rationality:
Studying minds in environments.
(Views of rationality; adaptive views of cognition; approaches to studying environmental influenes)
Additional
session: What happens when we ignore environments (discussion)
Required Readings:
Todd, P.M., and Gigerenzer, G. (2000). Simple heuristics that make us smart. Behavioral and Brain Sciences, 23(5), 727-741.
Optional Readings:
Gigerenzer, G., and Fiedler, K. (draft manuscript). Minds in environments: The potential of an ecological approach to cognition.
Hertwig, R., and Todd, P.M. (2002). Heuristics. Encyclopedia of the Human Brain (vol. 2, pp. 449-460). New York: Academic Press.
Day 2: Main lecture: Making
decisions despite ignorance: The recognition heuristic
(How recognition is used; how recognition can work in groups; how recognition can structure its own environment)
Additional
session: How to make money without knowledge (discussion)
Required Readings:
Goldstein, D. G., & Gigerenzer, G. (2002). Models of ecological rationality: The recognition heuristic. Psychological Review, 109 (1), 75-90.
Optional Readings:
Todd, P.M., & Kirby, S. (2001). I like what I know: How recognition-based decisions can structure the environment. In J. Kelemen and P. Sosík (Eds.), Advances in Artificial Life: 6th European Conference Proceedings (ECAL 2001) (pp. 166-175). Berlin: Springer-Verlag.
Day 3: Main lecture: Simple heuristics for simultaneous decisions:
Take The Best and co.
(Heuristic building blocks; lexicographic decision mechanisms; when people use them; how to study them experimentally; learning cue orders)
Additional session: Experiments and simulations with simple heuristics
Required Readings:
Gigerenzer, G., & Goldstein, D. G. (1999). Betting on one good reason: The Take The Best heuristic. In G. Gigerenzer, P.M. Todd, and the ABC Research Group, Simple heuristics that make us smart (pp. 75-95). New York: Oxford University Press.
Optional Readings:
Rieskamp, J., & Hoffrage, U. (1999). When do people use simple heuristics and how do we know this? In G. Gigerenzer, P.M. Todd, & the ABC Research Group, Simple heuristics that make us smart (pp. 141-167). New York: Oxford University Press.
Day 4: Main lecture:
Mechanisms for sequential search: Finding mates and jobs
(Satisficing and search with aspiration levels; one-sided and mutual mate search; testing individual behavior against demography)
Additional
session: How to find a parking space (discussion)
Required Readings:
Todd, P.M., & Miller, G.F. (1999). From pride and prejudice to persuasion: Satisficing in mate search. In G. Gigerenzer, P.M. Todd, and the ABC Research Group, Simple heuristics that make us smart (pp. 287-308). New York: Oxford University Press.
Optional Readings:
Todd, P.M., Billari, F.C., and Simão, J. (submitted). Modeling the emergence
of social marriage patterns produced by individual mate-search heuristics. Submitted to American Journal of
Sociology.
Miller, G.F., and Todd, P.M. (1998).
Mate
choice turns cognitive. Trends in Cognitive Sciences, 2, 190-198.
Day 5: Main lecture: More is
not always better: The benefits of cognitive limitations
(Benefits of limited information and limited processing; starting small in language learning; covariation detection)
Additional
session: When can less be more? (discussion of paper topics)
Required Readings:
Hertwig, R., and Todd, P.M. (in press). More
is not always better: The benefits of cognitive limits. In L. Macchi and D. Hardman (Eds.), The psychology of reasoning and decision
making: A handbook. Chichester, UK: Wiley.
Assessment:
Students who wish to receive credit for this course should write a 10-page paper describing a possible decision heuristic used by people or other animals in their domain of expertise, exploring how heuristic building blocks and environment structure may interact to produce adaptive decisions and/or how cognitive limitations may be advantageous in this case, and indicating a possible experiment or simulation to investigate this heuristic mechanism.
Peter M. Todd
Peter M. Todd was born in Silicon Valley and studied mathematics, computer modeling, and cognitive science at Oberlin College, Cambridge University, and UC San Diego before receiving a PhD in psychology at Stanford University. His thesis research there, under David Rumelhart, used neural network models to explore the evolution of learning. After developing “artificial life” simulations while a postdoctoral researcher at the Rowland Institute for Science in Cambridge, MA, he began as an assistant professor of psychology at the University of Denver. In 1995 he moved to Munich to help found the Center for Adaptive Behavior and Cognition at the Max Planck Institute for Psychological Research. His research interests there and at the Center's new home in Berlin have focused on modeling the interactions between decision making and decision environments, including how the two interact and co-evolve over time. The Center's work in this line has culminated in the book Simple Heuristics That Make Us Smart (Gigerenzer, Todd, and the ABC Research Group; Oxford, 1999); in addition, Todd has coedited three books on neural network models in music and has written papers on topics ranging from social decision processes in rats to the impact of mate choice on macroevolution.