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...
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...
Enforced hill-climbing is an effective deterministic hillclimbing technique that deals with local optima using breadth-first search (a process called "basin flooding"). ...
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...
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...