99 search results - page 4 / 20 » Action Selection in Bayesian Reinforcement Learning |
IEAAIE
2001
Springer
13 years 10 months ago
2001
Springer
In this paper a combined use of reinforcement learning and simulated annealing is treated. Most of the simulated annealing methods suggest using heuristic temperature bounds as the...
IAT
2003
IEEE
13 years 11 months ago
2003
IEEE
A gradient-based method for both symmetric and asymmetric multiagent reinforcement learning is introduced in this paper. Symmetric multiagent reinforcement learning addresses the ...
AAMAS
2002
Springer
13 years 5 months ago
2002
Springer
In reinforcement learning, an agent tries to learn a policy, i.e., how to select an action in a given state of the environment, so that it maximizes the total amount of reward it ...
IJCAI
2007
13 years 7 months ago
2007
Deictic representation is a representational paradigm, based on selective attention and pointers, that allows an agent to learn and reason about rich complex environments. In this...
ACL
2009
13 years 3 months ago
2009
In this paper, we present a reinforcement learning approach for mapping natural language instructions to sequences of executable actions. We assume access to a reward function tha...