Methods for Competitive Co - evolution : Finding Opponents Worth

نویسندگان

  • Christopher D. Rosin
  • Richard K. Belew
چکیده

Co-evolution refers to the simultaneous evolution of two or more genetically distinct populations with coupled tness landscapes. In this paper we consider \competitive co-evolution," in which the tness of an individual in a \host" population is based on direct competition with individual(s) from a \par-asite" population. Competitive co-evolution is applied to three game-learning problems: Tic-Tac-Toe (TTT), Nim and a small version of Go. Two new techniques in competitive co-evolution are explored. \Competitive t-ness sharing" changes the way tness is measured , and \shared sampling" alters the way parasites are chosen for testing hosts. Experiments using TTT and Nim show a substantial improvement in performance when these methods are used. Preliminary results using co-evolution for the discovery of cellular au-tomata rules for playing Go are presented.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Methods for Competitive Co-Evolution: Finding Opponents Worth Beating

Co-evolution refers to the simultaneous evolution of two or more genetically distinct populations with coupled tness landscapes. In this paper we consider \competitive co-evolution," in which the tness of an individual in a \host" population is based on direct competition with individual(s) from a \parasite" population. Competitive co-evolution is applied to three game-learning problems: Tic-Ta...

متن کامل

Algorithms for Evolving No-Limit Texas Hold'em Poker Playing Agents

Computers have difficulty learning how to play Texas Hold’em Poker. The game contains a high degree of stochasticity, hidden information, and opponents that are deliberately trying to mis-represent their current state. Poker has a much larger game space than classic parlour games such as Chess and Backgammon. Evolutionary methods have been shown to find relatively good results in large state sp...

متن کامل

Visualising Co-evolution with CIAO Plots

In a previous paper [2], we introduced a number of visualization techniques that we had developed for monitoring the dynamics of artificial competitive co-evolutionary systems. One of these techniques involves evaluating the performance of an individual from the current population in a series of trials against opponents from all previous generations, and visualizing the results as a 2-d grid of...

متن کامل

Multiobjective Imperialist Competitive Evolutionary Algorithm for Solving Nonlinear Constrained Programming Problems

Nonlinear constrained programing problem (NCPP) has been arisen in diverse range of sciences such as portfolio, economic management etc.. In this paper, a multiobjective imperialist competitive evolutionary algorithm for solving NCPP is proposed. Firstly, we transform the NCPP into a biobjective optimization problem. Secondly, in order to improve the diversity of evolution country swarm, and he...

متن کامل

Materazzi effect and the strategic use of anger in competitive interactions.

We propose that individuals use anger strategically in interactions. We first show that in some environments angering people makes them more effective in competitions, whereas in others, anger makes them less effective. We then show that individuals anticipate these effects and strategically use the option to anger their opponents. In particular, they are more likely to anger their opponents wh...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 1995