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JAIR
2006
157views more  JAIR 2006»
14 years 9 months ago
Decision-Theoretic Planning with non-Markovian Rewards
A decision process in which rewards depend on history rather than merely on the current state is called a decision process with non-Markovian rewards (NMRDP). In decisiontheoretic...
Sylvie Thiébaux, Charles Gretton, John K. S...
ACG
2009
Springer
15 years 4 months ago
Plans, Patterns, and Move Categories Guiding a Highly Selective Search
In this paper we present our ideas for an Arimaa-playing program (also called a bot) that uses plans and pattern matching to guide a highly selective search. We restrict move gener...
Gerhard Trippen
SSD
2005
Springer
108views Database» more  SSD 2005»
15 years 3 months ago
On Trip Planning Queries in Spatial Databases
In this paper we discuss a new type of query in Spatial Databases, called the Trip Planning Query (TPQ). Given a set of points of interest P in space, where each point belongs to ...
Feifei Li, Dihan Cheng, Marios Hadjieleftheriou, G...
JAIR
2000
152views more  JAIR 2000»
14 years 9 months ago
Value-Function Approximations for Partially Observable Markov Decision Processes
Partially observable Markov decision processes (POMDPs) provide an elegant mathematical framework for modeling complex decision and planning problems in stochastic domains in whic...
Milos Hauskrecht
AIPS
2008
14 years 12 months ago
Stochastic Enforced Hill-Climbing
Enforced hill-climbing is an effective deterministic hillclimbing technique that deals with local optima using breadth-first search (a process called "basin flooding"). ...
Jia-Hong Wu, Rajesh Kalyanam, Robert Givan