73 search results - page 9 / 15 » Incremental Learning of Planning Operators in Stochastic Dom... |
ROBOCUP
2007
Springer
14 years 1 months ago
2007
Springer
Abstract. Two main challenges of robot action planning in real domains are uncertain action effects and dynamic environments. In this paper, an instance-based action model is lear...
AAAI
2010
13 years 9 months ago
2010
Relational Markov Decision Processes (MDP) are a useraction for stochastic planning problems since one can develop abstract solutions for them that are independent of domain size ...
IAT
2010
IEEE
13 years 5 months ago
2010
IEEE
When its human operator cannot continuously supervise (much less teleoperate) an agent, the agent should be able to recognize its limitations and ask for help when it risks making...
AIPS
2008
13 years 9 months ago
2008
Enforced hill-climbing is an effective deterministic hillclimbing technique that deals with local optima using breadth-first search (a process called "basin flooding"). ...
AI
1999
Springer
13 years 7 months ago
1999
Springer
A central problem in multistrategy learning systems is the selection and sequencing of machine learning algorithms for particular situations. This is typically done by the system ...