181 search results - page 31 / 37 » State Space Reduction For Hierarchical Reinforcement Learnin... |
CI
2005
13 years 7 months ago
2005
Autonomous agents that learn about their environment can be divided into two broad classes. One class of existing learners, reinforcement learners, typically employ weak learning ...
AAMAS
2007
Springer
14 years 1 months ago
2007
Springer
Learning Automata (LA) were recently shown to be valuable tools for designing Multi-Agent Reinforcement Learning algorithms. One of the principal contributions of LA theory is that...
ICASSP
2008
IEEE
14 years 1 months ago
2008
IEEE
Repair or error-recovery strategies are an important design issue in Spoken Dialogue Systems (SDSs) - how to conduct the dialogue when there is no progress (e.g. due to repeated A...
IROS
2008
IEEE
14 years 1 months ago
2008
IEEE
—Multi-robot reinforcement learning is a very challenging area due to several issues, such as large state spaces, difficulty in reward assignment, nondeterministic action selecti...
JAIR
2007
13 years 7 months ago
2007
In this paper we present a general, flexible framework for learning mappings from images to actions by interacting with the environment. The basic idea is to introduce a feature-...