Representations of Space and Time in the Maximization of Information Flow in the Perception-Action Loop

DOI10.1162/neco.2007.19.9.2387zbMath1274.92008OpenAlexW2119794086WikidataQ51909895 ScholiaQ51909895MaRDI QIDQ5440975

Alexander S. Klyubin, Daniel Polani, Chrystopher L. Nehaniv

Publication date: 5 February 2008

Published in: Neural Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1162/neco.2007.19.9.2387

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Neural biology (92C20)

Related Items (3)

Behavioral analysis of differential Hebbian learning in closed-loop systems ⋮ INFORMATION FLOWS IN CAUSAL NETWORKS ⋮ Pursuit of food \textit{versus} pursuit of information in a Markovian perception-action loop model of foraging

Cites Work

• A Mathematical Theory of Communication
• Future paths for integer programming and links to artificial intelligence
• Locality of Global Stochastic Interaction in Directed Acyclic Networks
• Finite State Automata Resulting from Temporal Information Maximization and a Temporal Learning Rule
• On Information and Sufficiency

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