Contingency-Aware Exploration in Reinforcement Learning.
Jongwook ChoiYijie GuoMarcin MoczulskiJunhyuk OhNeal WuMohammad NorouziHonglak LeePublished in: ICLR (Poster) (2019)
Keyphrases
- reinforcement learning
- active exploration
- exploration strategy
- action selection
- model based reinforcement learning
- exploration exploitation
- markov decision processes
- autonomous learning
- function approximation
- model free
- exploration exploitation tradeoff
- temporal difference
- state space
- machine learning
- multi agent
- robotic control
- control problems
- reinforcement learning algorithms
- dynamic programming
- multi agent reinforcement learning
- stochastic approximation
- markov decision process
- learning algorithm
- data mining
- balancing exploration and exploitation
- real time
- policy search
- genetic algorithm
- supervised learning
- objective function
- partially observable
- information visualization
- database
- learning classifier systems
- mobile robot
- learning problems
- transfer learning
- optimal policy