A law in a multiagent system is a set of constraints imposed on agents' behaviours to avoid undesirable outcomes. The paper considers two types of laws: useful laws that, if followed, completely eliminate the undesirable outcomes and gap-free laws that guarantee that at least one agent can be held responsible each time an undesirable outcome occurs. In both cases, we study the problem of finding a law that achieves the desired result by imposing the minimum restrictions. We prove that, for both types of laws, the minimisation problem is NP-hard even in the simple case of one-shot concurrent interactions. We also show that the approximation algorithm for the vertex cover problem in hypergraphs could be used to efficiently approximate the minimum laws in both cases.
翻译:多智能体系统中的法律是一组施加于智能体行为的约束,旨在避免不良结果。本文考虑两种类型的法律:若被遵守则能完全消除不良结果的有效法律,以及确保每次不良结果发生时至少有一个智能体可被追究责任的零间隙法律。针对这两种情况,我们研究了通过施加最小限制来实现预期结果的法律设计问题。我们证明,对于这两种法律类型,即使在单次并发交互的简单场景中,最小化问题也是NP难的。我们还表明,超图中顶点覆盖问题的近似算法可用于高效地近似这两种情况下的最小法律。