73 search results - page 8 / 15 » Incremental Learning of Planning Operators in Stochastic Dom... |
ICML
1996
IEEE
14 years 8 months ago
1996
IEEE
Some of the most successful recent applications of reinforcement learning have used neural networks and the TD algorithm to learn evaluation functions. In this paper, we examine t...
ICML
2009
IEEE
14 years 8 months ago
2009
IEEE
Reinforcement Learning methods for controlling stochastic processes typically assume a small and discrete action space. While continuous action spaces are quite common in real-wor...
DAGSTUHL
2007
13 years 9 months ago
2007
The ways in which an agent’s actions affect the world can often be modeled compactly using a set of relational probabilistic planning rules. This paper addresses the problem of ...
ICML
2006
IEEE
14 years 8 months ago
2006
IEEE
Knowledge-based planning methods offer benefits over classical techniques, but they are time consuming and costly to construct. There has been research on learning plan knowledge ...
GECCO
2005
Springer
14 years 1 months ago
2005
Springer
In this paper we present a genetic algorithm applied to the problem of mission planning for Joint Suppression of Enemy Air Defenses (JSEAD) in support of air strike operations. Th...