The description of environment is a precondition of agent learning.
环境的描述是智能体学习的先决条件。
The new Agent learning model can be applied in some problems of the combinatorics.
给出了该学习模型在组合数学问题求解中的应用。
This paper gives a comprehensive overview about agent learning algorithms used in economic complexity system research.
对经济复杂性系统研究文献中常见的主体学习算法进行了一个全面的梳理。
Conclusion the comprehensive intervention could develop multi-agent learning ability of ld children, so as to improve their academic condition. The intervening technique is worth extended application.
结论综合干预训练能提高学习困难儿童多元学习能力，从而改善学业状况，值得推广应用。
Campers who sign up for the 2-week secret agent camp can get to know about the life of real secret agents by learning strategies and military skills on the paintball field.
报名参加为期2周的特工训练营的学员可以在彩弹场上学习战术和军事技能，了解真正的特工生活。
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。
Based on soccer robot simulation as its research platform, this paper studies the learning of high level strategy of multi-agent adversarial system.
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。
As the foundation of the research, the paper starts from discussing the meaning of the mechanism of the learning agent, defines the conception of learning agent and analyzes the components.
作为整个研究的基础，文章首先从学习代理基本内涵出发，对学习代理机制进行了界定，分析了学习代理的内涵与构成。
The agent has a high intelligence and can improve the learning ability according to the dynamic environment with the ability of Q learning.
学习使智能体具有较高的智能性，可以通过提高自己的学习能力适应不断变化的动态环境。
This paper discusses that as cognitive tool agent influences peoples learning action from both theoretical and practical aspects.
该文从理论和实践两个角度探讨了智能主体作为认知工具对人类学习的影响。
Due to the theoretical limitation that it assumes that an environment is Markovian, traditional reinforcement learning algorithms cannot be applied directly to multi-agent system.
由于强化学习理论的限制，在多智能体系统中马尔科夫过程模型不再适用，因此不能把强化学习直接用于多智能体的协作学习问题。
We discuss the situation of WWW information retrieval and then propound the total design of a retrieval intelligent agent pattern. We also study the knowledge learning agent and its algorithm.
在简要论述了WWW信息检索的现状并给出了一个检索智能代理模型的总体设计并对知识学习代理及其算法进行了研究。
MAXQ, a hierarchical reinforcement learning method for multi-agent system, is proposed in recent years.
MAXQ分层多智能体学习方法是近年来被提出的一种新方法。
The issue of cooperation learning for autonomous micro-mobile robot is the main problem of multi-agent robot system theory.
自主微小型移动机器人的协作学习研究是多智能体机器人系统理论的主要研究方向。
Nature would not think that learning is a boring class or another silly thing! Therefore, the class humor is an indispensable flavoring agent!
自然就不会觉得学习或者上课是一件乏味又无聊的事儿！
Grid; Distance Education; Learning Support System; Mobile Agent; Model.
网格；远程教育；学习支持系统；移动代理；模型。
With continuous experience accumulation in interactive play, the agent self-learning subsystem is mainly used for autonomic learning of game-agent to improve playing capability.
机器自学习子系统主要进行博弈主体的自主学习，通过对弈的交互过程不断积累经验，提高下棋的能力。
The agent self-learning subsystem implements the agent self-play training mode and the human-agent training mode.
机器自学习子系统实现了机器自对弈训练模式和人机对弈训练模式。
According to the functional interfaces, the system can be divided into three parts: the testing subsystem, the agent self-learning subsystem and the human-agent game-playing subsystem.
系统按功能界面划分为三个部分：测试子系统、机器自学习子系统和人机对弈子系统。
Tis paper presents two-layer reinforcement learning method for multi-agent cooperation.
提出了多智能体协作的两层强化学习方法。
Learning 4 sets of production unit: MTBE, fractional distillation, cracking and cracking by catalytic agent.
实习期间学习的四套装置为MTBE，气体分馏，重整和催化裂化装置。
Learning 4 sets of production unit: MTBE, fractional distillation, cracking and cracking by catalytic agent.
实习期间学习的四套装置为MTBE，气体分馏，重整和催化裂化装置。
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