93 search results - page 9 / 19 » Learning action models for multi-agent planning |
NIPS
1993
13 years 8 months ago
1993
While exploring to nd better solutions, an agent performing online reinforcement learning (RL) can perform worse than is acceptable. In some cases, exploration might have unsafe, ...
AAAI
2010
13 years 9 months ago
2010
The selection of the action to do next is one of the central problems faced by autonomous agents. In AI, three approaches have been used to address this problem: the programming-b...
ICML
1990
IEEE
13 years 11 months ago
1990
IEEE
Given an adequate simulation model of the task environment and payoff function that measures the quality of partially successful plans, competition-based heuristics such as geneti...
ATAL
2010
Springer
13 years 8 months ago
2010
Springer
A central problem in artificial intelligence is to choose actions to maximize reward in a partially observable, uncertain environment. To do so, we must learn an accurate model of ...
ICML
2008
IEEE
14 years 8 months ago
2008
IEEE
Partially Observable Markov Decision Processes (POMDPs) have succeeded in planning domains that require balancing actions that increase an agent's knowledge and actions that ...