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cs.AI2023★ 1 cited
Optimize Planning Heuristics to Rank, not to Estimate Cost-to-Goal
Leah Chrestien, Tomás Pevný, Stefan Edelkamp +1
In imitation learning for planning, parameters of heuristic functions are optimized against a set of solved problem instances. This work revisits the necessary and sufficient condi…
cs.AI2021
Heuristic Search Planning with Deep Neural Networks using Imitation, Attention and Curriculum Learning
Leah Chrestien, Tomas Pevny, Antonin Komenda +1
Learning a well-informed heuristic function for hard task planning domains is an elusive problem. Although there are known neural network architectures to represent such heuristic…