A cultural sensitive agent for human-computer negotiation

Galit Haim, Ya'akov Gal, Sarit Kraus, Michele Gelfand

نتاج البحث: نتاج بحثي من مؤتمرمحاضرةمراجعة النظراء

ملخص

People's cultural background has been shown to affect the way they reach agreements in negotiation and how they fulfill these agreements. This paper presents a novel agent design for negotiating with people from different cultures. Our setting involved an alternating-offer protocol that allowed parties to choose the extent to which they kept each of their agreements during the negotiation. A challenge to designing agents for such setting is to predict how people reciprocate their actions over time despite the scarcity of prior data of their behavior across different cultures. Our methodology addresses this challenge by combining a decision theoretic model with classical machine learning techniques to predict how people respond to offers, and the extent to which they fulfill agreements. The agent was evaluated empirically by playing with 157 people in three countries - Lebanon, the U.S., and Israel - in which people are known to vary widely in their negotiation behavior. The agent was able to outperform people in all countries under conditions that varied how parties depended on each other at the onset of the negotiation. This is the first work to show that a computer agent can learn to outperform people when negotiating in three countries representing different cultures.

اللغة الأصليةالإنجليزيّة
الصفحات504-511
عدد الصفحات8
حالة النشرنُشِر - 1 يناير 2012
الحدث11th International Conference on Autonomous Agents and Multiagent Systems 2012: Innovative Applications Track, AAMAS 2012 - Valencia, أسبانيا
المدة: ٤ يونيو ٢٠١٢٨ يونيو ٢٠١٢

!!Conference

!!Conference11th International Conference on Autonomous Agents and Multiagent Systems 2012: Innovative Applications Track, AAMAS 2012
الدولة/الإقليمأسبانيا
المدينةValencia
المدة٤/٠٦/١٢٨/٠٦/١٢

All Science Journal Classification (ASJC) codes

  • !!Artificial Intelligence

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