56 search results - page 1 / 12 » Q-Learning in Continuous State and Action Spaces |
IROS
2008
IEEE
13 years 11 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...
AROBOTS
1999
13 years 4 months ago
1999
We use reinforcement learning (RL) to compute strategies for multiagent soccer teams. RL may pro t signi cantly from world models (WMs) estimating state transition probabilities an...
ATAL
2003
Springer
13 years 9 months ago
2003
Springer
This paper presents an action selection framework based on an assemblage of self-organizing neural networks called Cooperative Extended Kohonen Maps. This framework encapsulates t...
AUSAI
1999
Springer
13 years 8 months ago
1999
Springer
Abstract. Q-learning can be used to learn a control policy that maximises a scalar reward through interaction with the environment. Qlearning is commonly applied to problems with d...
IROS
2007
IEEE
13 years 10 months ago
2007
IEEE
— In this paper, we present an approach that applies the reinforcement learning principle to the problem of learning height control policies for aerial blimps. In contrast to pre...