Psychotherapy AI Companion with Reinforcement Learning Recommendations and Interpretable Policy Dynamics.
Baihan LinGuillermo A. CecchiDjallel BouneffoufPublished in: WWW (Companion Volume) (2023)
Keyphrases
- reinforcement learning
- optimal policy
- policy search
- markov decision process
- action selection
- artificial intelligence
- function approximators
- machine learning
- partially observable environments
- partially observable
- dynamical systems
- reinforcement learning algorithms
- function approximation
- actor critic
- action space
- reward function
- control policies
- markov decision problems
- reinforcement learning problems
- policy iteration
- markov decision processes
- policy evaluation
- policy gradient
- approximate dynamic programming
- state and action spaces
- decision problems
- control policy
- knowledge representation
- expert systems
- dynamic model
- state space
- partially observable domains
- ai systems
- learning algorithm
- intelligent systems
- temporal difference
- recommender systems
- long run
- decision process
- case based reasoning
- rl algorithms
- learning process
- john mccarthy
- average reward
- multi agent
- model free
- dynamic programming
- control problems
- transfer learning
- transition model
- inverse reinforcement learning
- learning tasks
- knowledge based systems
- continuous state
- optimal control
- reinforcement learning methods
- recommendation systems
- lecture notes in artificial intelligence