Enhancing Reinforcement Learning with Label-Sensitive Reward for Natural Language Understanding.
Kuo LiaoShuang LiMeng ZhaoLiqun LiuMengge XueZhenyu HuHonglin HanChengguo YinPublished in: CoRR (2024)
Keyphrases
- natural language understanding
- reinforcement learning
- text understanding
- semantic analysis
- language understanding
- natural language
- knowledge representation
- state space
- dialogue system
- eligibility traces
- semantic representations
- function approximation
- spoken dialog systems
- machine learning
- reinforcement learning algorithms
- natural language processing
- model free
- reward function
- abductive reasoning
- multi agent
- optimal policy
- partially observable environments
- learning algorithm
- temporal difference
- learning agent
- lexical knowledge
- artificial intelligence
- markov decision processes
- dynamic programming
- expert systems
- high level