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Agent
- 实现Agent,绕墙走的功能,实现了图形化界面.点中按钮<AddWall>或<AddBlock>,使其处于按下状态,然后就可以在左边的矩形区域内通过点击鼠标左键设定墙或障碍物. 另外,还可以设定一组障碍物,方法是:先在 左上角按下鼠标左键,然后按住鼠标左键,拖动鼠标到所需的右下角,松开鼠标左键,这样,左上角和右下角之间的矩形区域就都被设成了障碍物
agent
- 通过智能agent间的协作，模拟解决吸尘器吸地板灰尘的问题，达到在最短时间内完成最好的洗尘效果。
RoboCup.rar
- 硕士生王磊毕业设计论文，全面讲述robocup agent 的设计和原理。,robocup agent designe...
search
- A Pacman agent needs to efficiently find paths through a maze, either to reach a particular location or collect remaining food quickly. In this project, you will build general search algorithms and apply them to Pacman scenarios. The code for t
AgentPersonMachineInteract
- 人机对话系统一直是人工智能领域内的研究热点，随着语音技术的日渐成熟，对话管理逐渐被认为是对话系统的关键问题，是整个系统的核心功能体现。由于种种限制，目前的人机对话系统大多是面向单个任务领域内的对话，而且只能在单机上运行，很少考虑对话过程涉及的多主题、主题切换、主题间的信息共享，以及对系统的复杂功能进行任务分解，使分解后的各个功能模块能运行在不同终端上通过通信合作实现更加强大的功能，使得系统易于扩展。 Agent技术是解决这些问题的最好方法，利用Agent技术可以很容易地实现任务的分解，多Ag
Multi-AgentGA
- Multi-Agent采购系统的遗传优化研究-Multi-Agent procurement system optimization study of the genetic
MultiAgentSystems
- 第13讲 智能Agent及多Agent系统 Chapter 13 Intelligent Agent & Multi-Agent Systems 徐从富 浙江大学人工智能研究所 -Article 13 stresses Intelligent Agent and Multi-Agent System Chapter 13 Intelligent Agent
Agentbasedbilateralalgorithm.
- 双边多议题协商是一个复杂的动态交互过程。解决Agent 在对环境和对方信息不全知的情况下通过协商达成一致并最大化自身效用是非常重要的。 -Bilateral multi-issue consultations is a complex process of dynamic interaction. Solve the Agent in the environment and the other incomplete information to know where to reach agr
DataMining
- 数据挖掘中与智能agent的结合，希望有用-Data mining and intelligent agent combination, I hope useful
TeamBots
- TeamBots 是一个可移植的多代理机器人仿真器，它可以支持动态环境中多代理控制系统的仿真，并可以提供可视化功能。-TeamBots is a portable multi-agent robot simulator, which can support a dynamic environment control system of multi-agent simulation, and can provide visualization capabilities.
Multiagent_Systems_and_Distributed_AI
- 介绍分布式人工智能的不错的入门书籍，主要利用分布式人工智能技术来构建multi－agent系统-Distributed artificial intelligence good introduction introductory books, the main use of distributed artificial intelligence technologies to build multi-agent system ... ...
Q_learning
- 强化学习是人工智能中策略学习的一种，基于预期最大利益原则。和博弈论有密切的关系，也是多主体系统学习的常用方法。-Reinforcement learning is a kind of artificial intelligence in the strategic study, based on the principle of best interests is expected. And game theory are closely related, but also multi-agen
TestTC5_SendingMessagesComplicated
- 利用terracotta进行agent的分配,agent之间能互发信息-implement the assigning of the agent, use agent to send and receive messages
Usithod
- 利用聚类分析法改进的多Agent协作强化学习方法-Using cluster analysis to improve collaborative multi-Agent Reinforcement Learning Method
Agent-src-JADE
- 实现三个Agent（消防员、医护员、警察），展示了当意外事件发生时候，Agent之间协调的作用-Achieve three Agent (firefighters, medical workers, police), shows the time when the accident occurred, Agent coordination role between the
waa
- WSN目标跟踪的移动Agent路由算法WSN target tracking routing algorithm for mobile Agent-WSN target tracking routing algorithm for mobile Agent
Taxi-route--based-on-multi-agent
- 基于多Agent的机场场面最优滑行路径算法-Taxi route optimization algorithm of airport surface based on multi agent
agent
- 基于agent图的脆性仿真程序，研究对象是船舶电力系统-Agent-based simulation program brittle graphs, study the ship power system
anoopajnt-(2)
- multi agent systems implimentation
Matlab code for multi-agent control
- 多智能体的编队控制，适合多智能体的编队或一致性研究的初学者学习(Multi-Agent Formation Control, Suitable for Initial Scholars of Multi-Agent Formation or Consistency Research)