Metastrategies in Large-Scale Bargaining Settings

Author:

Hennes Daniel1,Jong Steven De2,Tuyls Karl3,Gal Ya’akov (Kobi)4

Affiliation:

1. European Space Agency

2. TNO, The Netherlands

3. University of Liverpool, United Kingdom

4. Ben-Gurion University of the Negev, Israel

Abstract

This article presents novel methods for representing and analyzing a special class of multiagent bargaining settings that feature multiple players, large action spaces, and a relationship among players’ goals, tasks, and resources. We show how to reduce these interactions to a set of bilateral normal-form games in which the strategy space is significantly smaller than the original settings while still preserving much of their structural relationship. The method is demonstrated using the Colored Trails (CT) framework, which encompasses a broad family of games and has been used in many past studies. We define a set of heuristics (metastrategies) in multiplayer CT games that make varying assumptions about players’ strategies, such as boundedly rational play and social preferences. We show how these CT settings can be decomposed into canonical bilateral games such as the Prisoners’ Dilemma, Stag Hunt, and Ultimatum games in a way that significantly facilitates their analysis. We demonstrate the feasibility of this approach in separate CT settings involving one-shot and repeated bargaining scenarios, which are subsequently analyzed using evolutionary game-theoretic techniques. We provide a set of necessary conditions for CT games for allowing this decomposition. Our results have significance for multiagent systems researchers in mapping large multiplayer CT task settings to smaller, well-known bilateral normal-form games while preserving some of the structure of the original setting.

Funder

EU FP7 FET

Israeli Science Foundation

Publisher

Association for Computing Machinery (ACM)

Subject

Artificial Intelligence,Theoretical Computer Science

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A Negotiation Framework with Strategies Based on Agent Preferences;2017 21st International Conference on Control Systems and Computer Science (CSCS);2017-05

2. Space Debris Removal: A Game Theoretic Analysis;Games;2016-08-11

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