A cooperative network game efficiently solved via an ant colony optimization approach

Authors:
Pablo Romero;Franco Robledo;Pablo Rodríguez-Bocca;Darío Padula;María Elisa Bertinat
Affiliations:
Facultad de Ingeniería, Universidad de la República, Uruguay;Facultad de Ingeniería, Universidad de la República, Uruguay;Facultad de Ingeniería, Universidad de la República, Uruguay;Facultad de Ingeniería, Universidad de la República, Uruguay;Facultad de Ingeniería, Universidad de la República, Uruguay
Venue:
ANTS'10 Proceedings of the 7th international conference on Swarm intelligence
Year:
2010

Citing 3
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Abstract

In this paper, a Cooperative Network Game (CNG) is introduced. In this game, all players have the same goal: display a video content in real time, with no cuts and low buffering time. Inspired in cooperation and symmetry, all players should apply the same strategy, resulting in a fair play. For each strategy we shall define a score, and the search of the best one characterizes a Combinatorial Optimization Problem (COP). In this research we show that this search can be translated into a suitable Assymmetric Traveling Salesman Problem (ATSP). An Ant Colony Optimization (ACO) approach is defined, obtaining highly competitive solutions for the CNG. Finally, we play the game in a real context, using a new strategy in a Peer-to-Peer (P2P) platform, obtaining better results than previous strategies.