Randall D. Beer
Indiana University
145 Papers
1.7K Citations
Randall D. Beer is an academic researcher from Indiana University. The author has contributed to research in topics: Artificial neural network & Computer science. The author has an hindex of 42, co-authored 139 publications. Previous affiliations of Randall D. Beer include Case Western Reserve University.
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Papers
The brain has a body: adaptive behavior emerges from interactions of nervous system, body and environment.
Hillel J. Chiel,Randall D. Beer +1 more
TL;DR: Computational neuroethology, which jointly models neural control and periphery of animals, is a promising methodology for understanding adaptive behavior.
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A dynamical systems perspective on agent-environment interaction
TL;DR: A general theoretical framework for the synthesis and analysis of autonomous agents is sketched, in which an agent and its environment are modeled as two coupled dynamical systems whose mutual interaction is in general jointly responsible for the agent's behavior.
675
Dynamical approaches to cognitive science.
TL;DR: Three contrasting examples of work in this area that address the lexical and grammatical structure of language, Piaget's classic 'A-not-B' error, and active categorical perception in an embodied, situated agent are reviewed.
657
•Posted Content
Nonnegative Decomposition of Multivariate Information
Paul L. Williams,Randall D. Beer +1 more
TL;DR: This work reconsider from first principles the general structure of the information that a set of sources provides about a given variable and proposes a definition of partial information atoms that exhaustively decompose the Shannon information in a multivariate system in terms of the redundancy between synergies of subsets of the sources.
The Dynamics of Active Categorical Perception in an Evolved Model Agent
TL;DR: A model agent whose "nervous system" was evolved using a genetic algorithm to catch circular objects and to avoid diamond-shaped ones is studied to illustrate how the perspective and tools of dynamical systems theory can be applied to the analysis of situated, embodied agents capable of minimally cognitive behavior.
550