2 research outputs found
The Likeability-Success Tradeoff: Results of the 2nd Annual Human-Agent Automated Negotiating Agents Competition
We present the results of the 2nd Annual Human-Agent League of the Automated Negotiating Agent Competition. Building on the success of the previous year's results, a new challenge was issued that focused exploring the likeability-success tradeoff in negotiations. By examining a series of repeated negotiations, actions may affect the relationship between automated negotiating agents and their human competitors over time. The results presented herein support a more complex view of human-agent negotiation and capture of integrative potential (win-win solutions). We show that, although likeability is generally seen as a tradeoff to winning, agents are able to remain well-liked while winning if integrative potential is not discovered in a given negotiation. The results indicate that the top-performing agent in this competition took advantage of this loophole by engaging in favor exchange across negotiations (cross-game logrolling). These exploratory results provide information about the effects of different submitted 'black-box' agents in human-agent negotiation and provide a state-of-the-art benchmark for human-agent design.</p
Challenges and Main Results of the Automated Negotiating Agents Competition (ANAC) 2019
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