Category：Award｜Publishing : September 27, 2019
Professor Takayuki Ito
Project Assistant Professor Ryuta Arisaka
Best Paper Award
IJCAI 2019 Workshop on Agent-based Complex Automated Negotiations (ACAN)
Numerical Abstract Persuasion Argumentation for Expressing Concurrent Multi-Agent Negotiations
A paper submitted to the workshop "12th International Workshop on Agent-based Complex Automated Negotiations (ACAN2019) " held at the 28th International Joint Conference on Artificial intelligence (IJCAI2019) Selected as "Excellent Paper" and awarded "Best Paper Award".
Abstract: A negotiation process by 2 agents e1 and e2 can be interleaved by another negotiation process between, say, e1 and e3. The interleaving may alter the resource allocation assumed at the inception of the first negotiation process. Existing proposals for argumentation-based negotiations have focused primarily on two-agent bilateral negotiations, but scarcely on the concurrency of multi-agent negotiations. To fill the gap, we presented a novel argumentation theory, basing its development on abstract persuasion argumentation which is an abstract argumentation formalism with a dynamic relation. Incorporating into it numerical information and a mechanism of handshakes among members of the dynamic relation, we showed that the extended theory adapted well to concurrent multi-agent negotiations over scarce resources.
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