73 search results - page 11 / 15 » Incremental Learning of Planning Operators in Stochastic Dom... |
JAIR
2011
13 years 2 months ago
2011
Markovian processes have long been used to model stochastic environments. Reinforcement learning has emerged as a framework to solve sequential planning and decision-making proble...
KR
1989
Springer
13 years 11 months ago
1989
Springer
In this work we extend the work of Dean, Kaelbling, Kirman and Nicholson on planning under time constraints in stochastic domains to handle more complicated scheduling problems. I...
EXACT
2007
13 years 9 months ago
2007
In order to assist a power plant operator to face unusual situations, we have developed an intelligent assistant that explains the suggested commands generated by an MDP-based pla...
HRI
2007
ACM
13 years 11 months ago
2007
ACM
Intelligent planning algorithms such as the Partially Observable Markov Decision Process (POMDP) have succeeded in dialog management applications [10, 11, 12] because of their rob...
ICCBR
2009
Springer
14 years 2 months ago
2009
Springer
Case-based planning (CBP) systems are based on the idea of reusing past successful plans for solving new problems. Previous research has shown the ability of meta-reasoning approac...