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אקדמי בכיר

A study of computational and human strategies in revelation games

Noam Peled, Ya'akov Kobi Gal, Sarit Kraus

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.

שפת פרסום אנגלית
דפים 321-328
סטטוס פרסום פורסם - 01.01.2011

Keywords

Human-robot/agent interaction
Negotiation

ASJC Scopus subject areas

Artificial Intelligence
קבצים וקישורים אחרים
Link to publication in Scopus