458 search results - page 41 / 92 » Q-Decomposition for Reinforcement Learning Agents |
AAAI
2006
13 years 10 months ago
2006
Reinforcement learning problems are commonly tackled with temporal difference methods, which attempt to estimate the agent's optimal value function. In most real-world proble...
FLAIRS
2003
13 years 10 months ago
2003
1 Reinforcement learning has become a widely used methodology for creating intelligent agents in a wide range of applications. However, its performance deteriorates in tasks with s...
AAMAS
2007
Springer
14 years 3 months ago
2007
Springer
Abstract. Reinforcement learning (RL) is a widely used learning paradigm for adaptive agents. There exist several convergent and consistent RL algorithms which have been intensivel...
ICML
2010
IEEE
13 years 10 months ago
2010
IEEE
Abstract--Reinforcement learning (RL) research typically develops algorithms for helping an RL agent best achieve its goals-however they came to be defined--while ignoring the rela...
SGAI
2004
Springer
14 years 2 months ago
2004
Springer
We introduce a new class of Reinforcement Learning algorithms designed to operate in perceptual spaces containing images. They work by classifying the percepts using a computer vi...