CS348 FS2013 - Iterated Rock, Paper, Scissors: A Coevolutionary Genetic Programming Approach

The goal of this assignment set is for you to become familiarized with (I) unambigously formulating complex problems in terms of optimization, (II) implementing an Evolutionary Algorithm (EA) of the Coevolutionary and Genetic Programming (GP) persuasions, (III) conducting scientific experiments involving EAs, (IV) statistically analyzing experimental results from stochastic algorithms, and (V) writing proper technical reports. The problem that you will be solving is writing an EA to coevolve agents competing in the Iterated Rock, Paper, Scissors (I-RPS) environment with a GP representation. This problem is representative of a large and very important class of problems which require the identification of system models such as controllers, programs, or equations. An example of the latter is symbolic regression which attempts to identify a system model based on a limited number of observations of the system’s behavior; classic mathematical techniques for symbolic regression have certain inherent limitations which GP can overcome. Employing GP to evolve controllers for I-RPS agents is also a perfect illustration of how GP works while avoiding many of the complications of evolving full blown computer programs. This problem is also representative of a large and important class of problems where fitness is based on the interaction of individuals in one or more populations, so fitness is relative rather than absolute. These are individual assignments and plagiarism will not be tolerated. You must write your code from scratch in one of the approved programming languages. You are free to use libraries/toolboxes/etc, except search/optimization/EA specific ones.