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.
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Romero, P., Robledo, F., Rodríguez-Bocca, P., Padula, D., Bertinat, M.E. (2010). A Cooperative Network Game Efficiently Solved via an Ant Colony Optimization Approach. In: Dorigo, M., et al. Swarm Intelligence. ANTS 2010. Lecture Notes in Computer Science, vol 6234. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15461-4_29
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DOI: https://doi.org/10.1007/978-3-642-15461-4_29
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