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» Learning Heuristic Functions from Relaxed Plans
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ICML
1990
IEEE
15 years 1 months ago
Explanations of Empirically Derived Reactive Plans
Given an adequate simulation model of the task environment and payoff function that measures the quality of partially successful plans, competition-based heuristics such as geneti...
Diana F. Gordon, John J. Grefenstette
UAI
2008
14 years 11 months ago
Dyna-Style Planning with Linear Function Approximation and Prioritized Sweeping
We consider the problem of efficiently learning optimal control policies and value functions over large state spaces in an online setting in which estimates must be available afte...
Richard S. Sutton, Csaba Szepesvári, Alborz...
AIPS
2008
15 years 3 days 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
ICCBR
2009
Springer
15 years 4 months ago
Improving Reinforcement Learning by Using Case Based Heuristics
This work presents a new approach that allows the use of cases in a case base as heuristics to speed up Reinforcement Learning algorithms, combining Case Based Reasoning (CBR) and ...
Reinaldo A. C. Bianchi, Raquel Ros, Ramon Ló...
AIPS
2004
14 years 11 months ago
An Empirical Analysis of Some Heuristic Features for Local Search in LPG
LPG is a planner that performed very well in the last International planning competition (2002). The system is based on a stochastic local search procedure, and it incorporates se...
Alfonso Gerevini, Alessandro Saetti, Ivan Serina