AntTAG : a further study

AntTAG in [4], which combines ant search and GGGP, is a promising new method for program automatic synthesis. This paper studied the behavior of AntTAG on a specific symbolic regression problem. Based on observations, we slightly tailored AntTAG for this specific problem. This tailored version showed impressive performance. Experiments using AntTAG on more challenging symbolic regressions have been conducted. AntTAG significantly outperformed its GP counterpart, TAGGGP [6].

[1]  Marco Dorigo,et al.  Ant system: optimization by a colony of cooperating agents , 1996, IEEE Trans. Syst. Man Cybern. Part B.

[2]  Marco Dorigo,et al.  From Natural to Artificial Swarm Intelligence , 1999 .

[3]  Mark Craven,et al.  Refining the Structure of a Stochastic Context-Free Grammar , 2001, IJCAI.

[4]  Una-May O'Reilly,et al.  Genetic Programming II: Automatic Discovery of Reusable Programs. , 1994, Artificial Life.

[5]  Hussein A. Abbass,et al.  AntTAG: a new method to compose computer programs using colonies of ants , 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).

[6]  Aravind K. Joshi,et al.  Tree-Adjoining Grammars , 1997, Handbook of Formal Languages.

[7]  Nguyen Xuan Hoai,et al.  A Framework For Tree-Adjunct Grammar Guided Genetic Programming , 2001 .

[8]  T. Stützle,et al.  MAX-MIN Ant System and local search for the traveling salesman problem , 1997, Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97).

[9]  Marco Dorigo,et al.  The ant colony optimization meta-heuristic , 1999 .

[10]  Aravind K. Joshi,et al.  Tree Adjunct Grammars , 1975, J. Comput. Syst. Sci..