Abstract
Revelation games are bilateral bargaining games in which agents may choose to truthfully reveal their private information before engaging in multiple rounds of negotiation. They are analogous to real-world situations in which people need to decide whether to disclose information such as medical records or university transcripts when negotiating over health plans and business transactions. This paper presents an agent-design that is able to negotiate proficiently with people in a revelation game with different dependencies that hold between players. The agent modeled the social factors that affect the players' revelation decisions on people's negotiation behavior. It was empirically shown to outperform people in empirical evaluations as well as agents playing equilibrium strategies. It was also more likely to reach agreement than people or equilibrium agents. Categories and Subject Descriptors 1.2.11 [Distributed Artificial Intelligence] General Terms Experimentation.
Original language | English |
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Pages | 321-328 |
Number of pages | 8 |
State | Published - 2011 |
Event | 10th International Conference on Autonomous Agents and Multiagent Systems 2011, AAMAS 2011 - Taipei, Taiwan, Province of China Duration: 2 May 2011 → 6 May 2011 |
Conference
Conference | 10th International Conference on Autonomous Agents and Multiagent Systems 2011, AAMAS 2011 |
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Country/Territory | Taiwan, Province of China |
City | Taipei |
Period | 2/05/11 → 6/05/11 |
Keywords
- Human-robot/agent interaction
- Negotiation