Handling non-local dead-ends in Agent Planning Programs

Handling non-local dead-ends in Agent Planning Programs

Lukas Chrpa, Nir Lipovetzky, Sebastian Sardina

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence
Main track. Pages 971-978. https://doi.org/10.24963/ijcai.2017/135

We propose an approach to reason about agent planning programs with global information. Agent planning programs can be understood as a network of planning tasks, accommodating long-term goals, non-terminating behaviors, and interactive execution. We provide a technique that relies on reasoning about ``global" dead-ends and that can be incorporated to any planning-based approach to agent planning problems. In doing so, we also introduce the notion of online execution of such planning structures. We provide experimental evidence suggesting the technique yields significant benefits.
Keywords:
Knowledge Representation, Reasoning, and Logic: Action, Change and Causality
Agent-based and Multi-agent Systems: Agent Theories and Models
Combinatorial & Heuristic Search: Meta-Reasoning and Meta-heuristics