搜索资源列表
CEExamPrepKiteBook
- 在本准备指南（用于 Microsoft 认证技术专家 (TS) 考试 70-571 的“Windows Embedded CE 6.0 开发” ，发布于 2008 年五月）中，您可以发现有关 CE 操作系统、 开发工具、和概念等的很多信息。我们非常兴奋于考试 70-571 的启动。它标志着 Windows Embedded CE 成功故事的另一个重要里程碑。现在，作为第一次，嵌入式开 发人员有能力评定和展示他们基于 Windows Embedded 技术开发嵌入式解决方案的技
MCTS.Self-Paced.Training.Kit.Exam.70-536.dot.NET.
- MCTS.Self-Paced.Training.Kit.Exam.70-536.dot.NET.Framework.2.0.A.zip
SQL2005_Implementation_Maintenance
- Guito certification . MCTS 70-431 - SQL Server 2005 Implementation and Maintenance.-Guito to certification . MCTS 70-431- SQL Server 2005 Implementation and Maintenance.
ExamSimulator
- Microsoft Exam,MCTS, 70 -536
Microsoft.Press.MCTS.Self.Paced.Training.Kit.Exam
- WCF Certification, Certificación en WCF
MCTS.Self-Paced.Training.Kit.Exam.70-667
- Exam 70-667: Pro: Configuring Microsoft SharePoint 2010
MCTS(70-562)_ASP.Net_3.5_Development
- MCTS ASP.NET 3.5 Web Development
Strategy
- 人工智能导论课程大作业，四子棋策略dll文件源码。使用并实现了MCTS算法。每一步计算时间为4秒。-Assignmeng of Introduction to Artificial Intelligence, Connect4 game strategy dll sources. Use and implement MCTS algorithm. Every step of the calculation time is 4 seconds.
UCT
- 蒙特卡洛树算法，基于python实现。游戏编程- Monte Carlo tree search (MCTS) is a heuristic search algorithm for some kinds of decision processes, most notably those employed in game play
mcts-java-1
- 蒙特卡洛树搜索算法，基于Java实现，有需要的下载- Monte Carlo tree search (MCTS) is a heuristic search algorithm for some kinds of decision processes, most notably those employed in game play
mcts
- java 蒙特卡罗树搜索源代码 java 蒙特卡罗树搜索源代码-java mcts
mcts-cpp-master
- 蒙特卡洛树搜索，树搜索算法。可自动平衡树的深度和广度搜索(Monte Carlo algorithm)
MCST
- python实现的，基于蒙特卡洛树搜索下五子棋(Monte Carlo tree search Gobang, python implementation)
MonteCarloTreeSearch-master
- 用MCTS算法做的游戏Tic-Tac-Toe，很简单，想研究MCTS的可以下载运行参考。(Using MCTS algorithm to do the game Tic-Tac-Toe, very simple, want to study MCTS can download operation reference)
MCTS
- 用蒙特卡洛树搜索的办法实现黑白棋落子决策问题(Search with Monte Carlo tree to achieve Riversi decision problem)
AlphaGo MCTS.py
- 实现AlphaGo MCTS的基本版本，通过一些状态、策略函数等(This is a "pure" implementation of the AlphaGo MCTS algorithm in that it is not specific to the game of Go; everything in this file is implemented generically with respect to some state, actions, policy fu