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Modelling Multi-Agent Epistemic Planning in ASP

机译：在ASP中建模多元患者认知规划

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摘要

Designing agents that reason and act upon the world has always been one of the main objectives of the Artificial Intelligence community. While for planning in "simple" domains the agents can solely rely on facts about the world, in several contexts,e.g., economy, security, justice and politics, the mere knowledge of the world could be insufficient to reach a desired goal. In these scenarios,epistemicreasoning,i.e., reasoning about agents' beliefs about themselves and about other agents' beliefs, is essential to design winning strategies. This paper addresses the problem of reasoning in multi-agent epistemic settings exploiting declarative programming techniques. In particular, the paper presents an actual implementation of a multi-shotAnswer Set Programming-based planner that can reason in multi-agent epistemic settings, called PLATO (ePistemic muLti-agentAnswer seTprogramming sOlver). The ASP paradigm enables a concise and elegant design of the planner, w.r.t. other imperative implementations, facilitating the development of formal verification of correctness. The paper shows how the planner, exploiting an ad-hoc epistemic state representation and the efficiency of ASP solvers, has competitive performance results on benchmarks collected from the literature.
机译：设计代理商，理性和对世界的行为一直是人工智能界的主要目标之一。虽然在“简单”域名中规划，但代理商可以完全依赖于世界的事实，在几个背景下，例如，经济，安全，正义和政治，仅仅对世界的知识可能不足以达到预期的目标。在这些情景中，关于代理人对自己以及其他代理人的信念的推理，对自己的信念，对自己来说是必不可少的。本文涉及利用声明规划技术的多智能经纪认知设置推理问题。特别是，本文提出了一种基于多枪手集编程的计划程序的实际实现，可以推理多种代理认知设置，称为柏拉图（认知多AgentAnswer SetProgramment Solver）。 ASP PARADIGM能够简洁而优雅地设计Planner，W.R.T.其他命令实施，促进了正式验证正确性的发展。本文展示了策划者，利用临时认识状态表征和ASP求解器的效率，对从文献中收集的基准具有竞争性绩效结果。

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