环境的描述是智能体学习的先决条件。
The description of environment is a precondition of agent learning.
多智能体的协调与合作。
第二，提出了一种基于多智能体的作战模型。
Secondly, a kind of multi-agent based combat model is proposed.
研究表明，多智能体技术非常适合于实现集合保护。
Research results show that multi-agent system (MAS) is suitable to implement aggregate protection.
提出了基于智能体方法的化工过程运行系统的集成策略。
An agent-based approach for integration of chemical process operation systems is proposed.
本文实现了一个基于多智能体结构的车间调度原型系统。
A shop scheduling prototype system based on multi agent architecture is implemented.
研究基于自主行为智能体的月球车运动规划与控制方法。
An approach based on autonomous behavior agent of lunar rover motion planning and controlling is presented.
也许可我们也许不少以创造出一个智能体来帮我们做些事。
It could be an intelligence that could help us difficulti intellig aspect do things.
设计了一种基于协作协进化算法的分层式的智能体体系结构。
A layered architecture is constructed based on cooperative co-evolution algorithm.
它能很好地解决智能体在随机状态环境下寻找最优动作的问题。
It can solve the problem very well, which is how an agent searches the best action in random state environment.
其要点是因为更为智能的智能体不仅能够想象，还能够创造出我们想象不到的东西。
The point is that as more intelligent beings they'll be capable of not just imagining, but creating things we can't even dream about.
多智能体系统的智能体大都处在复杂、时变、信息动态不完备的环境中。
Agents in multi-agent system are always in complex, dynamic and not self-contained.
文章提出了利用协作协进化来实现多智能体机器人之间协作的一种机制。
This paper proposes a mechanism which realizes the cooperation of multi-agent by cooperative co-evolution.
建立智能体的个性化模型一直是心理学家和计算机学家的一个热门话题。
Setting up the computer model of personality of virtual character is a hot topic of psychology and computer science all the time.
它为计算机（或“智能体”，即Agent，译者注）执行一项操作赋予某些分值。
The idea is that the computer (or the "agent") can get a certain amount of value from performing some actions.
从初步试验结果可知，模型提高了协商效率，增加了协商智能体的效用。
Initial experimental results indicate that the model improves the efficiency of negotiations and increases the utility.
首先探讨了基于多智能体的分布式智能控制在工业控制应用中的意义和特点。
First, the significance and characteristics of the application of multi-agent based distributed intelligent control to industry control are discussed.
本文基于多智能体系统理论，研究了多智能体机器人系统的底层实时调度问题。
This paper will study under layered real-time scheduling problem, which is based on the theory of MAS (Multi-agent System).
如何通过情感来提高虚拟智能体的智能性和可信服性已成为亟待解决的关键问题。
Therefore, how to use emotion to enhance the intelligence and believability of virtual agent is an urgent issue to solve.
开发数码傀儡的三种基本思路的代表是：古典人工智能、人工生命和可信智能体。
Three kinds of basic thought of developing the digital puppet are: Classical artificial intelligence, artificial life and believable intelligent body.
研究了基于多智能体的作战模型的建模工作流程，确定了各个步骤中的主要工作；
The modeling process of the multi-agent based combat model is discussed, and the main task of every step is ascertained.
为了实现虚拟企业的业务过程管理，引入智能体，设计了一种新型工作流控制模型。
To implement business process management in virtual enterprises, a kind of new workflow control model was proposed by introduction of Agent.
针对多智能体静态任务分配存在的不足，提出了一种足球机器人动态任务分配算法。
A dynamic assignment allocation algorithm is presented to overcome the disadvantage of the static assignment allocation in robot soccer.
本文以足球仿真机器人系统为研究平台，研究多智能体对抗系统的高层策略学习问题。
Based on soccer robot simulation as its research platform, this paper studies the learning of high level strategy of multi-agent adversarial system.
将多智能体技术应用于交互式进化计算领域，提出一种新的交互式多智能体进化算法。
By introducing multi-agent technique into the domain of interactive evolutionary computation, a new interactive multi-agent evolutionary algorithm (IMAGA) was developed.
情感作为人类具有智能的一个重要体现，是创建可信服的虚拟智能体不可或缺的环节。
Emotion is an important aspect of human intelligence and is shown to play a significant role in creating virtual agent.
本文在详细了解和研究多智能体系统的基础之上讨论并实现了一个多智能体机器人系统。
After detailed understanding and long-term study of multi-agent system, this thesis discussed and realized a multi-agent robot system.
基于马尔科夫过程的强化学习作为一种在线学习方式，能够很好地应用于单智能体环境中。
Reinforcement learning based on Markov decision process is a way of on-line learning, which can be applied to single agent environment.
基于马尔科夫过程的强化学习作为一种在线学习方式，能够很好地应用于单智能体环境中。
Reinforcement learning based on Markov decision process is a way of on-line learning, which can be applied to single agent environment.
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