Literature DB >> 28918312

(Reinforcement?) Learning to forage optimally.

Nils Kolling1, Thomas Akam2.   

Abstract

Foraging effectively is critical to the survival of all animals and this imperative is thought to have profoundly shaped brain evolution. Decisions made by foraging animals often approximate optimal strategies, but the learning and decision mechanisms generating these choices remain poorly understood. Recent work with laboratory foraging tasks in humans suggest their behaviour is poorly explained by model-free reinforcement learning, with simple heuristic strategies better describing behaviour in some tasks, and in others evidence of prospective prediction of the future state of the environment. We suggest that model-based average reward reinforcement learning may provide a common framework for understanding these apparently divergent foraging strategies.
Copyright © 2017 Elsevier Ltd. All rights reserved.

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Year:  2017        PMID: 28918312     DOI: 10.1016/j.conb.2017.08.008

Source DB:  PubMed          Journal:  Curr Opin Neurobiol        ISSN: 0959-4388            Impact factor:   6.627


  9 in total

1.  Altering gain of the infralimbic-to-accumbens shell circuit alters economically dissociable decision-making algorithms.

Authors:  Brian M Sweis; Erin B Larson; A David Redish; Mark J Thomas
Journal:  Proc Natl Acad Sci U S A       Date:  2018-06-18       Impact factor: 11.205

2.  The effect of apathy and compulsivity on planning and stopping in sequential decision-making.

Authors:  Jacqueline Scholl; Hailey A Trier; Matthew F S Rushworth; Nils Kolling
Journal:  PLoS Biol       Date:  2022-03-31       Impact factor: 8.029

3.  Performance-gated deliberation: A context-adapted strategy in which urgency is opportunity cost.

Authors:  Maximilian Puelma Touzel; Paul Cisek; Guillaume Lajoie
Journal:  PLoS Comput Biol       Date:  2022-05-26       Impact factor: 4.779

Review 4.  Foraging for foundations in decision neuroscience: insights from ethology.

Authors:  Dean Mobbs; Pete C Trimmer; Daniel T Blumstein; Peter Dayan
Journal:  Nat Rev Neurosci       Date:  2018-07       Impact factor: 34.870

5.  Mice learn to avoid regret.

Authors:  Brian M Sweis; Mark J Thomas; A David Redish
Journal:  PLoS Biol       Date:  2018-06-21       Impact factor: 8.029

6.  Prospection, Perseverance, and Insight in Sequential Behavior.

Authors:  Nils Kolling; Jacqueline Scholl; Adam Chekroud; Hailey A Trier; Matthew F S Rushworth
Journal:  Neuron       Date:  2018-09-05       Impact factor: 17.173

Review 7.  State-change decisions and dorsomedial prefrontal cortex: the importance of time.

Authors:  Nils Kolling; Jill X O'Reilly
Journal:  Curr Opin Behav Sci       Date:  2018-08

8.  Foraging as an evidence accumulation process.

Authors:  Jacob D Davidson; Ahmed El Hady
Journal:  PLoS Comput Biol       Date:  2019-07-24       Impact factor: 4.475

Review 9.  Revisiting foraging approaches in neuroscience.

Authors:  Sam Hall-McMaster; Fabrice Luyckx
Journal:  Cogn Affect Behav Neurosci       Date:  2019-04       Impact factor: 3.282

  9 in total

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