Nested Monte-Carlo Search

نویسنده

  • Tristan Cazenave
چکیده

Many problems have a huge state space and no good heuristic to order moves so as to guide the search toward the best positions. Random games can be used to score positions and evaluate their interest. Random games can also be improved using random games to choose a move to try at each step of a game. Nested Monte-Carlo Search addresses the problem of guiding the search toward better states when there is no available heuristic. It uses nested levels of random games in order to guide the search. The algorithm is studied theoretically on simple abstract problems and applied successfully to three different games: Morpion Solitaire, SameGame and 16x16 Sudoku.

برای دانلود رایگان 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

Nested Monte-Carlo Expression Discovery

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 transfo...

متن کامل

Monte-Carlo Bus Regulation

Bctusbdu ̋In this paper we want to minimize passengers waiting times at the bus stops by making buses wait at a stop. We compare a simple rule based approach to a MonteCarlo method for this problem. When allocated enough time, the Monte-Carlo method gives better results. If the passengers arrivals and the bus travel times are known, the best algorithm is nested Monte-Carlo search with memorizati...

متن کامل

Nested Monte-Carlo Tree Search for Online Planning in Large MDPs

Monte-Carlo Tree Search (MCTS) is state of the art for online planning in large MDPs. It is a best-first, sample-based search algorithm in which every state in the search tree is evaluated by the average outcome of Monte-Carlo rollouts from that state. These rollouts are typically random or directed by a simple, domain-dependent heuristic. We propose Nested Monte-Carlo Tree Search (NMCTS), in w...

متن کامل

Distributed Nested Rollout Policy for SameGame

Nested Rollout Policy Adaptation (NRPA) is a Monte Carlo search heuristic for puzzles and other optimisation problems. It achieves state of the art performance on several games including SameGame. In this paper, we design several parallel and distributed NRPA-based search techniques, and we provide number of experimental insights about their execution. Finally, we use our best implementation to...

متن کامل

High-Diversity Monte-Carlo Tree Search

For combinatorial search in single-player games nested Monte-Carlo search is an apparent alternative to algorithms like UCT that are applied in two-player and general games. To trade exploration with exploitation the randomized search procedure intensifies the search with increasing recursion depth. If a concise mapping from states to actions is available, the integration of policy learning has...

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

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2009