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Indiana University Bloomington
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Faculty

Colin Allen
Provost Professor, Department of History and Philosophy of Science

Dr. Allen is interested in a broad spectrum of philosophical and methodological questions about the study of animal behavior and cognition, particularly in the area known as "cognitive ethology". These issues include the applicability of mentalistic language to nonhuman animals, such as whether animals have concepts, reasoning capacities, and even consciousness. As a philosopher, he is only rarely involved directly in empirical work on animals, instead focusing at a theoretical level on the differences between ethological and psychological approaches to animal cognition and the contrasting roles that evolutionary theory plays in each science. Recent and ongoing projects include an attempt to combine functional, behavioral, and neurological approaches to the study of animal pain, an investigation of the role that non-experimental observation of animal behavior plays in cognitive ethology, and analyses of specific debates on topics such as the capacity for transitive inference in animals and the function of "mirror neurons" in monkeys.

Robert Goldstone
Chancellor's Professor, Psychological and Brain Sciences

Dr. Goldstone's laboratory explores human group behavior from the perspective of complex systems analyses. Just as interacting ants create colony architectures that no ant intends, people create group-level behaviors that are not intended and may not be perceived by any person. Dr. Goldstone's laboratory draws parallels between animal and human group behavior to help us understand human behavior such as foraging for resources, the propagation of innovations, and coalition formation. They are also involved in developing agent-based computational models of empirically observed group behavior. To pursue their empirical work, Dr. Goldstone's laboratory has developed an experimental platform that allows many human participants to interact in real-time within a common virtual environment. Playable examples of their collective behavior experiments can be found at http://groups.psych.indiana.edu/. If there are an insufficient number of human players at any given moment, artificially intelligent “bots” are automatically deployed so that human players will have experiment partners. These “bots” are instantiations of their computational models of agent behavior in a group.

Peter M. Todd
Director, Cognitive Science Program
Professor, Cognitive Science
Professor, Informatics and Computing
Provost Professor, Psychological and Brain Sciences

Jonathon Crystal
Professor, Psychological and Brain Sciences
Director, Undergraduate Studies, Cognitive Science

Ellen Ketterson
Distinguished Professor, Biology and Gender Studies

Larry Yaeger
Professor Emeritus, Informatics and Computing

Professor Yaeger is primarily interested in machine intelligence, but has long believed and proclaimed that real progress in this area will only come from the evolution of an ever - increasing spectrum of intelligences, from the computational Aplysia to the computational lab rat and so on. His fundamental approach is to follow the course that led to the emergence of natural intelligence - the evolution of nervous systems in an ecology. Evolution because of its power to find solutions to any problem. Nervous systems because this is what natural evolution discovered and used in all known examples of biological intelligence. Ecology because intelligence is only of value - can only be selected for - if it helps an organism survive and reproduce within its ecological context. Given this focus, it is clear that an understanding of animal intelligence, including the mechanisms and characteristics of animal cognition, are essential to assessing the progress of the stated evolutionary goals. The experimental and analytical methods used for studying animal cognition are of direct value in studying artificial intelligence of the sort professor Yaeger is pursuing. He also expects the formal, philosophical methods used to understand and characterize animal cognition will someday be applicable to evolved machine intelligence.