73 search results - page 3 / 15 » Incremental Learning of Planning Operators in Stochastic Dom... |
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 ...
AIPS
2008
13 years 9 months ago
2008
Dynamic programming algorithms have been successfully applied to propositional stochastic planning problems by using compact representations, in particular algebraic decision diag...
AAAI
1994
13 years 8 months ago
1994
In this paper, we describe the partially observable Markov decision process pomdp approach to nding optimal or near-optimal control strategies for partially observable stochastic ...
AI
1999
Springer
13 years 7 months ago
1999
Springer
There are many different approaches to solving planning problems, one of which is the use of domain specific control knowledge to help guide a domain independent search algorithm. ...
PKDD
2009
Springer
14 years 2 months ago
2009
Springer
Probabilistic relational models are an efficient way to learn and represent the dynamics in realistic environments consisting of many objects. Autonomous intelligent agents that gr...