1236 search results - page 59 / 248 » Opposition-Based Reinforcement Learning |
ICML
2006
IEEE
14 years 10 months ago
2006
IEEE
For a Markov Decision Process with finite state (size S) and action spaces (size A per state), we propose a new algorithm--Delayed Q-Learning. We prove it is PAC, achieving near o...
AGENTS
2001
Springer
14 years 2 months ago
2001
Springer
This paper describes Icarus, an agent architecture that embeds a hierarchical reinforcement learning algorithm within a language for specifying agent behavior. An Icarus program e...
AAAI
1997
13 years 11 months ago
1997
This paper steps back from the standard infinite horizon formulation of reinforcement learning problems to consider the simpler case of finite horizon problems. Although finite ho...
COLT
2008
Springer
13 years 11 months ago
2008
Springer
We propose a model-based learning algorithm, the Adaptive Aggregation Algorithm (AAA), that aims to solve the online, continuous state space reinforcement learning problem in a de...
ATAL
2007
Springer
14 years 4 months ago
2007
Springer
Reinforcement learning is a popular and successful framework for many agent-related problems because only limited environmental feedback is necessary for learning. While many algo...