Bandit-Based Monte Carlo Optimization for Nearest Neighbors
نویسندگان
چکیده
منابع مشابه
Bandit Based Monte-Carlo Planning
For large state-space Markovian Decision Problems MonteCarlo planning is one of the few viable approaches to find near-optimal solutions. In this paper we introduce a new algorithm, UCT, that applies bandit ideas to guide Monte-Carlo planning. In finite-horizon or discounted MDPs the algorithm is shown to be consistent and finite sample bounds are derived on the estimation error due to sampling...
متن کاملPlaying Tetris Using Bandit-Based Monte-Carlo Planning
Tetris is a stochastic, open-ended board game. Existing artificial Tetris players often use different evaluation functions and plan for only one or two pieces in advance. In this paper, we developed an artificial player for Tetris using the bandit-based Monte-Carlo planning method (UCT). In Tetris, game states are often revisited. However, UCT does not keep the information of the game states ex...
متن کاملAdaptive Monte Carlo via Bandit Allocation
We consider the problem of sequentially choosing between a set of unbiased Monte Carlo estimators to minimize the mean-squared-error (MSE) of a final combined estimate. By reducing this task to a stochastic multi-armed bandit problem, we show that well developed allocation strategies can be used to achieve an MSE that approaches that of the best estimator chosen in retrospect. We then extend th...
متن کاملMonte Carlo-based optimization of a gamma probe system for sentinel lymph node mapping
Introduction: Sentinel lymph node biopsy (SLNB) is a standard surgical technique to identify sentinel lymph node (SLN) for the staging of early breast cancer. Nowadays, two methods are used for the identification of SLN: blue dye method aiding visually and radioactive dye using gamma detector. A wide range of gamma probe systems with different design and performance are used in...
متن کاملMonte Carlo Simulation and Population-Based Optimization
This paper briefly reviews some properties of Monte Carlo simulation and emphasizes the link to evolutionary computation. It shows how this connection can help to study evolutionary algorithms within a unified framework. It also gives some practical examples of implementation inspired from MOSES (the mutation-or-selection evolution strategy).
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Journal on Selected Areas in Information Theory
سال: 2021
ISSN: 2641-8770
DOI: 10.1109/jsait.2021.3076447