{
  "title": "ActiveInferants",
  "domain": "Entomology",
  "type": "Paper",
  "creators": [
    {
      "name": "Daniel A. Friedman"
    },
    {
      "name": "Alexander Tschantz"
    },
    {
      "name": "Maxwell J.D. Ramstead"
    },
    {
      "name": "Karl Friston"
    },
    {
      "name": "Axel Constant"
    }
  ],
  "description": "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 behavi...",
  "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 being applied across settings in theoretical biology and ethology. We specify and simulate a Markov decision process (MDP) model for ant colony foraging using the alternating T-maze paradigm, illustrating the model's ability to recover basic colony phenomena such as trail formation aft",
  "keywords": [
    "active inference",
    "ant foraging",
    "Markov decision process",
    "stigmergy",
    "T-maze",
    "collective behavior",
    "behavioral modeling",
    "eco-evo-devo"
  ],
  "methods": [
    {
      "name": "Active inference agent-based simulation",
      "description": "Applied active inference agent-based simulation approach"
    },
    {
      "name": "Markov decision process modeling of foraging",
      "description": "Applied markov decision process modeling of foraging approach"
    }
  ],
  "key_findings": [
    "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 behavi...."
  ],
  "related_papers": [
    "2016_AntGenetics",
    "2016_ForagingGene",
    "2017_MutAnts"
  ],
  "checked_at": "2026-07-01T20:50:01Z"
}