Automated Verification of Social Law Robustness in STRIPS. Erez Karpas, A. S. & Tennenholtz, M. In Proceedings of the 4th Workshop on Distributed and Multi-Agent Planning (DMAP-16), 2016.
abstract   bibtex   
Agents operating in a multi-agent system must consider not just their own actions, but also those of the other agents in the system. Artificial social systems are a well known means for coordinating a set of agents, without requiring centralized planning or online negotiation between agents. Artificial social systems enact a social law which restricts the agents from performing some actions under some circumstances. A good social law prevents the agents from interfering with each other, but does not prevent them from achieving their goals. However, designing good social laws, or even checking whether a proposed social law is good, are hard questions. In this paper, we take a first step towards automating these processes, by formulating criteria for good social laws in a multi-agent planning framework. We then describe an automated technique for verifying if a proposed social law meets these criteria, which is based on a compilation to classical planning.
@INPROCEEDINGS{dmap2016karpas,
author = {Erez Karpas, Alexander Shleyfman and Moshe Tennenholtz},
title = {Automated Verification of Social Law Robustness in STRIPS},
booktitle = {Proceedings of the 4th Workshop on Distributed and Multi-Agent Planning (DMAP-16)},
abstract = {Agents operating in a multi-agent system must consider not just their own actions, but also those of the other agents in the system. Artificial social systems are a well known means for coordinating a set of agents, without requiring centralized planning or online negotiation between agents. Artificial social systems enact a social law which restricts the agents from performing some actions under some circumstances. A good social law prevents the agents from interfering with each other, but does not prevent them from achieving their goals. However, designing good social laws, or even checking whether a proposed social law is good, are hard questions. In this paper, we take a first step towards automating these processes, by formulating criteria for good social laws in a multi-agent planning framework. We then describe an automated technique for verifying if a proposed social law meets these criteria, which is based on a compilation to classical planning.},
year = {2016}
}

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