资源论文Resolving Over-Constrained Conditional Temporal Problems Using Semantically Similar Alternatives

Resolving Over-Constrained Conditional Temporal Problems Using Semantically Similar Alternatives

2019-11-25 | |  45 |   38 |   0
Abstract In recent literature, several approaches have been developed to solve over-constrained travel planning problems, which are often framed as conditional temporal problems with discrete choices. These approaches are able to explain the causes of failure and recommend alternative solutions by suspending or weakening temporal constraints. While helpful, they may not be practical in many situations, as we often cannot compromise on time. In this paper, we present an approach for solving such over-constrained problems, by also relaxing non-temporal variable domains through the consideration of additional options that are semantically similar. Our solution, called Conflict-Directed Semantic Relaxation (CDSR), integrates a knowledge base and a semantic similarity calculator, and is able to simultaneously enumerate both temporal and domain relaxations in best-first order. When evaluated empirically on a range of urban trip planning scenarios, CDSR demonstrates a substantial improvement in flexibility compared to temporal relaxation only approaches.

上一篇:Hierarchical Finite State Controllers for Generalized Planning

下一篇:Commitment Semantics for Sequential Decision Making under Reward Uncertainty

用户评价
全部评价

热门资源

  • The Variational S...

    Unlike traditional images which do not offer in...

  • Stratified Strate...

    In this paper we introduce Stratified Strategy ...

  • Learning to learn...

    The move from hand-designed features to learned...

  • A Mathematical Mo...

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

  • Learning to Predi...

    Much of model-based reinforcement learning invo...