Document Type

Conference Proceeding

Publisher

IEEE

Faculty

Faculty of Health, Engineering and Science

School

School of Computer and Security Science

RAS ID

19200

Comments

This is an Author's Accepted Manuscript of: Ashlock D., & Hingston P. (2014). Tego - A framework for adversarial planning. Proceedings of the 2014 IEEE Congress on Evolutionary Computation, CEC 2014. (pp. 13-20). Beijing, China. IEEE. © 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Available here

Abstract

This study establishes a framework called ∗-Tego for a situation in which two agents are each given a set of players for a competitive game. Each agent places their players in an order. Players on each side at the same position in the order play one another, with the agent's score being the sum of their player's scores. The planning agents are permitted to simultaneous reorder their players in each of several stages. The reordering is termed competitive replanning. The resulting framework is scalable by changing the number of players and the complexity of the replanning process. The framework is demonstrated using iterated prisoner's dilemma on a set of twenty players. The system is first tested with one agent unable to change the order of its players, yielding an optimization problem. The system is then tested in a competitive co-evolution of planning agents. The optimization form of the system makes globally sensible assignments of players. The co-evolutionary version concentrates on matching particular high-payoff pairs of players with the agents repeatedly reversing one another's assignments, with the majority of players with smaller payoffs at risk are largely ignored.

DOI

10.1109/CEC.2014.6900498

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free_to_read

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