arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2008.03007cs.AI
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ASP中多Agent认知规划的建模

Modelling Multi-Agent Epistemic Planning in ASP

University of Udine(乌迪内大学);New Mexico State University(新墨西哥州立大学)

Alessandro Burigana, Francesco Fabiano, Agostino Dovier, Enrico Pontelli

摘要:

设计能够对世界进行推理和行动的智能体一直是人工智能社区的主要目标之一。虽然对于在“简单”域中的规划,智能体可以仅依赖于关于世界的事实,但在几个上下文中,例如,在经济、安全、司法和政治方面,仅仅对世界的了解可能不足以实现预期目标。在这些情况下,认知推理,即,推理代理人对自己的信念和其他代理人的信念,是设计获胜策略的关键。本文利用声明性编程技术解决了多智能体认知环境中的推理问题。特别是,本文提出了一个实际的实现多杆答案集编程为基础的规划,可以在多智能体认知设置,称为PLATO(ePistemic多智能体答案集编程sOlver)的原因。ASP范例使规划器的设计简洁而优雅,w.r.t.其他必要的实现,促进正确性的形式化验证的开发。本文展示了如何规划者,利用一个特设的认知状态表示和效率的ASP求解器,有竞争力的性能结果从文献中收集的基准。目前正在考虑让TPLP接受。

英文摘要:

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, epistemic reasoning, 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-shot Answer Set Programming-based planner that can reason in multi-agent epistemic settings, called PLATO (ePistemic muLti-agent Answer seT programming 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. It is under consideration for acceptance in TPLP.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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