Switching Competitors Reduces Win-Stay but Not Lose-Shift Behaviour: The Role of Outcome-Action Association Strength on Reinforcement Learning.
Vincent SrihaputKaylee CrapleweBenjamin J. DysonPublished in: Games (2020)
Keyphrases
- reinforcement learning
- action selection
- action space
- state action
- function approximation
- learning algorithm
- markov decision processes
- state space
- partially observable domains
- data sets
- functional roles
- internal state
- user behaviour
- model free
- optimal policy
- supervised learning
- dynamic programming
- temporal difference
- reward function
- reinforcement learning algorithms
- transfer learning
- multi agent reinforcement learning
- transition model
- policy search
- reward shaping
- e learning
- machine learning