TY - GEN
T1 - Challenges and Main Results of the Automated Negotiating Agents Competition (ANAC) 2019
AU - Aydoğan, Reyhan
AU - Baarslag, Tim
AU - Fujita, Katsuhide
AU - Mell, Johnathan
AU - Gratch, Jonathan
AU - de Jonge, Dave
AU - Mohammad, Yasser
AU - Nakadai, Shinji
AU - Morinaga, Satoshi
AU - Osawa, Hirotaka
AU - Aranha, Claus
AU - Jonker, Catholijn M.
N1 - Funding Information:
This work is part of the Veni research programme with project number 639.021.751, which is financed by the The Dutch Research Council (NWO). This work was partially funded by project LOGISTAR, under the E.U. Horizon 2020 research and innovation programme, Grant Agreement No. 769142. This research was also sponsored by the U.S. Army Research Office and was accomplished under Cooperative Agreement Number W911NF-20-2-0053. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Army Research Office or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation herein.
Publisher Copyright:
© 2020, Springer Nature Switzerland AG.
PY - 2020
Y1 - 2020
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85101310681&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85101310681&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-66412-1_23
DO - 10.1007/978-3-030-66412-1_23
M3 - Conference contribution
AN - SCOPUS:85101310681
SN - 9783030664114
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 366
EP - 381
BT - Multi-Agent Systems and Agreement Technologies - 17th European Conference, EUMAS 2020, and 7th International Conference, AT 2020, Revised Selected Papers
A2 - Bassiliades, Nick
A2 - Chalkiadakis, Georgios
A2 - de Jonge, Dave
PB - Springer Science and Business Media Deutschland GmbH
T2 - 17th European Conference on Multi-Agent Systems, EUMAS 2020, and 7th International Conference on Agreement Technologies, AT 2020
Y2 - 14 September 2020 through 15 September 2020
ER -