Article

Learning and Forgetting Using Reinforced Bayesian Change Detection

2018-04-06

Abstract excerpt

Agents living in volatile environments must be able to detect changes in contingencies while refraining to adapt to unexpected events that are caused by noise. In Reinforcement Learning (RL) frameworks, this requires learning rates that adapt to past reliability of the model. The observation that behavioural flexibility in animals tends to decrease following prolonged training in stable environment provides experi...

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Literature Corpus work: 93058575-d449-544a-8a15-f7b633be2094
DOI: 10.1101/294959

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