Evolving a Ms. PacMan Controller Using Grammatical Evolution
نویسندگان
چکیده
In this paper we propose an evolutionary approach capable of successfully combining rules to play the popular video game, Ms. PacMan. In particular we focus our attention on the benefits of using Grammatical Evolution to combine rules in the form of “if then perform ”. We defined a set of high-level functions that we think are necessary to successufully maneuver Ms. Pac-Man through a maze while trying to get the highest possible score. For comparison purposes, we used four Ms. Pac-Man agents, including a hand-coded agent, and tested them against three different ghosts teams. Our approach shows that the evolved controller achieved the highest score among all the other tested controllers, regardless of the ghost team used.
منابع مشابه
Constitution of Ms.PacMan player with critical-situation learning mechanism
We previously proposed evolutionary fuzzy systems of playing Ms.PacMan for the competitions. As a consequence of the evolution, reflective action rules such that PacMan tries to eat pills effectively until ghosts come close to PacMan are acquired. Such rules works well. However, sometimes it is too reflective so that PacMan go toward ghosts by herself in longer corridors. In this paper, a criti...
متن کاملGrammatical Evolution by Grammatical Evolution: The Evolution of Grammar and Genetic Code
This study examines the possibility of evolving the grammar that Grammatical Evolution uses to specify the construction of a syntactically correct solution. As the grammar dictates the space of symbols that can be used in a solution, its evolution represents the evolution of the genetic code itself. Results provide evidence to show that the coevolution of grammar and genetic code with a solutio...
متن کاملA Comparative Study of Genetic Programming and Grammatical Evolution for Evolving Data Structures
The research presented in the paper forms part of a larger initiative aimed at automatic algorithm induction using machine learning. This paper compares the performance of two machine learning techniques, namely, genetic programming and a variation of genetic programming, grammatical evolution, for automatic algorithm induction. The application domain used to evaluate both the approaches is the...
متن کاملEvolving Phonological Rules Using Grammatical Evolution
Phonetic transcription is a core procedure of continuous speech recognition systems and speech synthesizers. The more correct phonetic translation is the more successful applications using phonetic transcription are. Phonological rules translate text to graphemes. These rules significantly reduce size of databases with words and it’s phonetic transcription and speeds up transcription process. T...
متن کامل