Challenges and Main Results of the Automated Negotiating Agents Competition (ANAC) 2019
Reyhan Aydogan (TU Delft - Electrical Engineering, Mathematics and Computer Science, Özyeğin University)
Tim Baarslag (Centrum Wiskunde & Informatica (CWI), Universiteit Utrecht)
Katsuhide Fujita (Tokyo University of Agriculture and Technology, National Institute of Advanced Industrial Science and Technology (AIST))
Johnathan Mell (University of Southern California)
Jonathan Gratch (University of Southern California)
Dave de Jonge (Institut d'Investigació en Intel·ligència Artificial - CSIC)
Yasser Mohammad (NEC Corporation, National Institute of Advanced Industrial Science and Technology (AIST))
Shinji Nakadai (NEC Corporation, National Institute of Advanced Industrial Science and Technology (AIST))
Satoshi Morinaga (National Institute of Advanced Industrial Science and Technology (AIST), NEC Corporation)
Hirotaka Osawa (University of Tsukuba)
Claus Aranha (University of Tsukuba)
Catholijn Jonker (TU Delft - Electrical Engineering, Mathematics and Computer Science)
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Abstract
The Automated Negotiating Agents Competition (ANAC) is a yearly-organized international contest in which participants from all over the world develop intelligent negotiating agents for a variety of negotiation problems. To facilitate the research on agent-based negotiation, the organizers introduce new research challenges every year. ANAC 2019 posed five negotiation challenges: automated negotiation with partial preferences, repeated human-agent negotiation, negotiation in supply-chain management, negotiating in the strategic game of Diplomacy, and in the Werewolf game. This paper introduces the challenges and discusses the main findings and lessons learnt per league.