Browsing by Author "Mohammad, Y."

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    The 13th international automated negotiating agent competition challenges and results
    (Springer, 2023) Aydoğan, Reyhan; Baarslag, T.; Fujita, K.; Hoos, H. H.; Jonker, C. M.; Mohammad, Y.; Renting, B. M.; Computer Science; AYDOĞAN, Reyhan
    An international competition for negotiating agents has been organized for years to facilitate research in agent-based negotiation and to encourage the design of negotiating agents that can operate in various scenarios. The 13th International Automated Negotiating Agents Competition (ANAC 2022) was held in conjunction with IJCAI2022. In ANAC2022, we had two leagues: Automated Negotiation League (ANL) and Supply Chain Management League (SCML). For the ANL, the participants designed a negotiation agent that can learn from the previous bilateral negotiation sessions it was involved in. In contrast, the research challenge was to make the right decisions to maximize the overall profit in a supply chain environment, such as determining with whom and when to negotiate. This chapter describes the overview of ANL and SCML in ANAC2022, and reports the results of each league, respectively.
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    Challenges and main results of the automated negotiating agents competition (ANAC) 2019
    (Springer, 2020) Aydoğan, Reyhan; Baarslag, T.; Fujita, K.; Mell, J.; Gratch, J.; de Jonge, D.; Mohammad, Y.; Nakadai, S.; Morinaga, S.; Osawa, H.; Aranha, C.; Jonker, C. M.; Computer Science; Bassiliades, N.; Chalkiadakis, G.; de Jonge, D.; AYDOĞAN, Reyhan
    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.