Field Report: Applying Monte Carlo Tree Search for Program Synthesis
نویسندگان
چکیده
Program synthesis aims to automatically generate an executable segment of code that satisfies a given set of criteria. Genetic programming has been widely studied for program synthesis. However, it has drawbacks such as code bloats and the difficulty in finer control over the growth of programs. This paper explores the possibility of applying Monte Carlo Tree Search (MCTS) technique to general purpose program synthesis. The exploratory study applies MCTS to synthesis of six small benchmarks using Java Bytecode instructions, and compares the results to those of genetic programming. The paper discusses the major challenges and outlines the future work.
منابع مشابه
Monte-Carlo Tree Search
representation of the game. It was programmed in LISP. Further use of abstraction was also studied by Friedenbach (1980). The combination of search, heuristics, and expert systems led to the best programs in the eighties. At the end of the eighties a new type of Go programs emerged. These programs made an intensive use of pattern recognition. This approach was discussed in detail by Boon (1990)...
متن کاملMonte-Carlo Hex
We present YOPT a program that plays Hex using Monte-Carlo tree search. We describe heuristics that improve simulations and tree search. We also address the combination of Monte-Carlo tree search with virtual connection search.
متن کاملMonte-Carlo Tree Search Solver
Recently, Monte-Carlo Tree Search (MCTS) has advanced the field of computer Go substantially. In this article we investigate the application of MCTS for the game Lines of Action (LOA). A new MCTS variant, called MCTS-Solver, has been designed to play narrow tactical lines better in sudden-death games such as LOA. The variant differs from the traditional MCTS in respect to backpropagation and se...
متن کاملParallel Monte-Carlo Tree Search
Monte-Carlo Tree Search (MCTS) is a new best-first search method that started a revolution in the field of Computer Go. Parallelizing MCTS is an important way to increase the strength of any Go program. In this article, we discuss three parallelization methods for MCTS: leaf parallelization, root parallelization, and tree parallelization. To be effective tree parallelization requires two techni...
متن کاملA new self-acquired knowledge process for Monte Carlo Tree Search
Computer Go is one of the most challenging field in Artificial Intelligence Game. In this area the use of Monte Carlo Tree Search has emerged as a very attractive research direction, where recent advances have been achieved and permitted to significantly increase programs efficiency. These enhancements result from combining tree search used to identify best next moves, and a Monte Carlo process...
متن کامل