Active Inferants: An Active Inference Framework for Ant Colony Behavior

Frontiers in Behavioral Neuroscience

Daniel Ari Friedman¹  Alec Tschantz⁴  Maxwell J. D. Ramstead⁷  Axel Constant⁸  Karl Friston⁹ 

[1] Active Inference Lab, University of California, Davis, Davis, CA, United States;Culture, Mind, and Brain Program, McGill University, Montreal, QC, Canada;Department of Entomology and Nematology, University of California, Davis, Davis, CA, United States;Department of Informatics, University of Sussex, Brighton, United Kingdom;Division of Social and Transcultural Psychiatry, Department of Psychiatry, McGill University, Montreal, QC, Canada;Sackler Centre for Consciousness Science, University of Sussex, Brighton, United Kingdom;Spatial Web Foundation, Los Angeles, CA, United States;Theory and Method in Biosciences, The University of Sydney, Sydney, NSW, Australia;Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom;

关键词: ants;    foraging;    active inference;    behavioral modeling;    collective behavior;    T-maze;   

DOI  :  10.3389/fnbeh.2021.647732

来源: DOAJ

【 摘 要 】

In this paper, we introduce an active inference model of ant colony foraging behavior, and implement the model in a series of in silico experiments. Active inference is a multiscale approach to behavioral modeling that is being applied across settings in theoretical biology and ethology. The ant colony is a classic case system in the function of distributed systems in terms of stigmergic decision-making and information sharing. Here we specify and simulate a Markov decision process (MDP) model for ant colony foraging. We investigate a well-known paradigm from laboratory ant colony behavioral experiments, the alternating T-maze paradigm, to illustrate the ability of the model to recover basic colony phenomena such as trail formation after food location discovery. We conclude by outlining how the active inference ant colony foraging behavioral model can be extended and situated within a nested multiscale framework and systems approaches to biology more generally.

【 授权许可】

Unknown