资源论文Domain Model Acquisition in the Presence of Static Relations in the LOP System

Domain Model Acquisition in the Presence of Static Relations in the LOP System

2019-11-25 | |  64 |   39 |   0
Abstract We present a new domain model acquisition algorithm, LOP, that induces static predicates by using a combination of the generalised output from LOCM2 and a set of optimal plans as input to the learning system. We observe that static predicates can be seen as restrictions on the valid groundings of actions. Without the static predicates restricting possible groundings, the domains induced by LOCM2 produce plans that are typically shorter than the true optimal solutions. LOP works by finding a set of minimal static predicates for each operator that preserves the length of the optimal plan.

上一篇:Buchi, Lindenbaum, Tarski: A Program Analysis Appetizer

下一篇:A Nearly-Linear Time Framework for Graph-Structured Sparsity

用户评价
全部评价

热门资源

  • The Variational S...

    Unlike traditional images which do not offer in...

  • Learning to Predi...

    Much of model-based reinforcement learning invo...

  • Stratified Strate...

    In this paper we introduce Stratified Strategy ...

  • A Mathematical Mo...

    Direct democracy, where each voter casts one vo...

  • Rating-Boosted La...

    The performance of a recommendation system reli...