Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Genetic programming for finite algebras
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Simulation-based approach to general game playing
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 1
Achieving master level play in 9×9 computer go
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 3
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Predicting prime numbers using cartesian genetic programming
EuroGP'07 Proceedings of the 10th European conference on Genetic programming
Efficient selectivity and backup operators in Monte-Carlo tree search
CG'06 Proceedings of the 5th international conference on Computers and games
Nested Monte-Carlo Search with simulation reduction
Knowledge-Based Systems
| Hi-index | 0.00 |
Nested Monte-Carlo search is a general algorithm that gives good results in single player games. Genetic Programming evaluates and combines trees to discover expressions that maximize a given evaluation function. In this paper Nested Monte-Carlo Search is used to generate expressions that are evaluated in the same way as in Genetic Programming. Single player Nested Monte-Carlo Search is transformed in order to search expression trees rather than lists of moves. The resulting program achieves state of the art results on multiple benchmark problems. The proposed approach is simple to program, does not suffer from expression growth, has a natural restart strategy to avoid local optima and is extremely easy to parallelize.