Active Inferants: An Active Inference Framework for Ant Colony Behavior.

ABSTRACT: 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 outli

SUBMITTER: Friedman DA 

PROVIDER: S-EPMC8264549 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature