What is Needed to Promote an Asynchronous Program Evolution in Genetic Programing?

Unlike a synchronous program evolution in the context of evolutionary computation that evolves individuals (i.e., programs) after evaluations of all individuals in each generation, this paper focuses on an asynchronous program evolution that evolves individuals during evaluations of each individual. To tackle this problem, we explore the mechanism that can promote an asynchronous program evolution by selecting a good individual without waiting for evaluations of all individuals, and investigates its effectiveness in genetic programming (GP) domain. The intensive experiments have revealed the following implications: (1) the program asynchronously evolved with the proposed mechanism can be completed with the shorter execution steps than the program asynchronously evolved without the proposed mechanism; and (2) the program asynchronously evolved with the proposed mechanism can be completed with mostly the same or shorter execution steps than the program synchronously evolved by the conventional GP.

[1]  John R. Koza,et al.  Genetic programming - on the programming of computers by means of natural selection , 1993, Complex adaptive systems.

[2]  Qingfu Zhang,et al.  MOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposition , 2007, IEEE Transactions on Evolutionary Computation.

[3]  Peter Nordin,et al.  Genetic programming - An Introduction: On the Automatic Evolution of Computer Programs and Its Applications , 1998 .

[4]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[5]  W. Banzhaf,et al.  1 Linear Genetic Programming , 2007 .

[6]  K. Takadama,et al.  Tierra-based space system for robustness of bit inversion and program evolution , 2007, SICE Annual Conference 2007.

[7]  Thomas S. Ray,et al.  An Approach to the Synthesis of Life , 1991 .

[8]  Tobias Glasmachers,et al.  A natural evolution strategy with asynchronous strategy updates , 2013, GECCO '13.

[9]  Hiroyuki Sato,et al.  Robustness to Bit Inversion in Registers and Acceleration of Program Evolution in On-Board Computer , 2011, J. Adv. Comput. Intell. Intell. Informatics.

[10]  Chris Langton,et al.  Artificial Life , 2017, Encyclopedia of Machine Learning and Data Mining.

[11]  Rainer Storn,et al.  Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces , 1997, J. Glob. Optim..

[12]  Andrew Lewis,et al.  Asynchronous Multi-Objective Optimisation in Unreliable Distributed Environments , 2009 .

[13]  Craig W. Reynolds.  An evolved, vision-based behavioral model of coordinated group motion , 1993 .