A Logic-Based Framework for Explainable Agent Scheduling Problems
A Logic-Based Framework for Explainable Agent Scheduling Problems
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DOI：
10.3233/faia230542
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发表时间：
2023
期刊：
影响因子：
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通讯作者：
S. Vasileiou;Borong Xu;William Yeoh
中科院分区：
文献类型：
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作者：
S. Vasileiou;Borong Xu;William Yeoh
.代理调度问题（ASP）在各种现实世界中很常见，需要可解释的决策过程来有效地将资源分配给多个代理，同时促进理解和信任。为了满足这一需求，本文提出了一个逻辑为基础的框架，在ASP提供可解释的决定。具体来说，该框架解决了两种类型的查询：原因寻求查询，解释调度决策背后的推理，以及修改寻求查询，提供指导，使不可行的决策可行。认识到隐私在多代理调度的重要性，我们引入了一个隐私损失函数，该函数用于测量解释中的隐私信息披露，从而在我们的框架中实现隐私保护方面。通过使用这个函数，我们引入了隐私感知解释的概念，并提出了一个算法来计算它们。实证评估表明，我们的方法的有效性和通用性。
. Agent Scheduling Problems (ASPs) are common in various real-world situations, requiring explainable decision-making processes to effectively allocate resources to multiple agents while fostering understanding and trust. To address this need, this paper presents a logic-based framework for providing explainable decisions in ASPs. Specifically, the framework addresses two types of queries: reason-seeking queries , which explain the reasoning behind scheduling decisions, and modification-seeking queries , which offer guidance on making infeasible decisions feasible. Acknowledging the importance of privacy in multi-agent scheduling, we introduce a privacy-loss function that measures the disclosure of private information in explanations, enabling a privacy-preserving aspect in our framework. By using this function, we introduce the notion of privacy-aware explanations and present an algorithm for computing them. Empirical evaluations demonstrate the effectiveness and versatility of our approach.