Abstract
An automated negotiator is an intelligent agent whose task is to reach the best possible agreement. We explore a novel approach to developing a negotiation strategy, a ‘domain-based approach’. Specifically, we use two domain parameters, reservation value and discount factor, to cluster the domain into different regions, in each of which we employ a heuristic strategy based on the notions of temporal flexibility and bargaining strength. Following the presentation of our cognitive and formal models, we show in an extensive experimental study that an agent based on that approach wins against the top agents of the automated negotiation competition of 2012 and 2013, and attained the second place in 2014.
Original language | English |
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Pages (from-to) | 597-616 |
Number of pages | 20 |
Journal | Journal of Experimental and Theoretical Artificial Intelligence |
Volume | 29 |
Issue number | 3 |
DOIs | |
State | Published - 4 May 2017 |
Keywords
- ANAC competition
- Bargaining
- automated negotiations
All Science Journal Classification (ASJC) codes
- Software
- Theoretical Computer Science
- Artificial Intelligence