强化学习算法的英文

• reinforcement learning algorithm

• "强化"英文翻译    strengthen; intensify; conso ...
• "学习"英文翻译    study; learn; emulate
• "算法"英文翻译    algorithm
• "强化式学习算法" 英文翻译 :    reinforcement learning algorithm
• "学习算法" 英文翻译 :    learning algorithm
• "回传式学习算法" 英文翻译 :    back propagation algorithm
• "线性再励学习算法" 英文翻译 :    linear reinforcement learning algorithm
• "收信碰撞预防学习算法" 英文翻译 :    rcala receiver conflict avoidance learning algorithm
• "强化学习系统" 英文翻译 :    reinforcement learning system
• "为便于强化学习" 英文翻译 :    for convenience of intensive study he has an intense intention of making friend with me
• "强化学校" 英文翻译 :    cram school
• "化学计算法" 英文翻译 :    stechiometry; stoichiometry
• "算法学习理论" 英文翻译 :    alt algorithmic learning theory
• "化学强化玻璃" 英文翻译 :    chemically strengtheed glass
• "增强化学发光" 英文翻译 :    enhanced chemiluminescence
• "个别化学习" 英文翻译 :    individualized learning
• "同化学习" 英文翻译 :    assimilative learning
• "网络化学习" 英文翻译 :    e-learning
• "性化学习" 英文翻译 :    individualized learning
• "强化式学习系统" 英文翻译 :    reinforcement learning system
• "化学强化沉淀处理" 英文翻译 :    chemically enhanced sedimentation process
• "强化学风化残积层" 英文翻译 :    loipon
• "强化学风化覆盖层" 英文翻译 :    loipon
• "增强化学气相沉积" 英文翻译 :    pcvd
• "反应和化学计算法" 英文翻译 :    chemical reactions and stoichiometry

• Q - learning method is an online reinforcement learning recently
  Q - learning算法是近期所提出的在线强化学习算法。
• A reinforcement learning algorithm based on process reward and prioritized sweeping is presented as interference solving strategy
  本文提出了基于过程奖赏和优先扫除的强化学习算法作为多机器人系统的冲突消解策略。
• ( 4 ) a new cooperation model called macm is presentd and based on this model , an improved distributed reinforcement learning algorithm is also proposed
  ( 4 )提出一种新的多agent协作模型macm及一种改进的分布式强化学习算法。
• The macrl - cc analyses the speciality of the system ’ s goal , then decomposes it , and , by using the commitment - and - conventions - based method , the system achieves cooperative problem solving betweem agents
  本文的主要成果及创新是,提出了两种多agent协同强化学习算法,并进行了实验验证。
• In this paper , we elaborate some domains an information agent involves , introduce reinforce learning into dynamic scheduling of searching engines , and realize intelligent scheduling of searching engines
  本文对信息agent所涉及的关键技术进行了比较深刻的研究，把强化学习算法引入到搜索引擎的动态调度中来，实现了搜索引擎的智能化调度。
• Comparisons of other nine strategies such as the algorithm based on global reward and q - learning , show that the presented algorithm based on process reward and prioritized sweeping can decrease interference , avoid deadlock and improve group performance
  结果表明所提出的基于过程奖赏和优先扫除的强化学习算法能显著减少冲突，避免死锁，提高系统整体性能。
• The reinforcement learning algorithm was also introduced , since it has some relations with the colony algorithm and can be need in the problem of scheduling . 4 . some new concepts and scheduling algorithms for batch chemical process were proposed in our studies
  由于蚁群算法与人工智能中的强化学习算法之间有着某种联系，同时强化学习近年来也应用于求解调度问题，因此本文也涉及到了一些强化学习的主要算法。
• 2 . study comparatively profoundly the theory of reinforce leaning , its main algorithms , and methods of improve its velocity , make use of modeling method of reinforce learning to build a scheduling model of searching engines , and gets better results . 3
  对强化学习算法的理论、主要算法和提高强化学习速度的方法进行了比较深刻的研究，并运用强化学习算法的建模方法建立起了一个搜索引擎调度模型，在实际应用中取得了比较好的效果。
• Reinforcement learning is an applicable machine learning method of agent state and knowledge . we combined rl and fuzzy logic together to make improvement on agent inner model and state denotation method . this fuzzy reinforcement learning method decreases the requirement of modeling precision and makes the algorithm more applicable
  论文的研究在现有强化学习算法的基础上，采用模糊建模的方法对于agent的内部模型和状态的表示方法进行改进，提出一种模糊强化学习算法，降低了agent学习对于精确模型和知识的要求，提高了算法的实用性。
• After introducing some basic concepts of agent 、 mas and multi - agents learning , the thesis analyses the research actuality and the future developmental directions of rl and multi - agent rl ( marl ) . furthermore , the theory and related learning algorithms of them are briefly introduced . on the basis of analyses of pursuit game , aimed at the individual action learner , the thesis extends the rl algorithm for single agent , proposes the macrl - cc algorithm . finally , aimed at the joint action learner , a team - stochastic - games - based ( tsgs - based ) framework for multi - agents cooperative rl is defined
  文章首先介绍了agent和多agent系统、以及多agent学习的一些基本概念,然后介绍了强化学习和多agent强化学习的研究现状和未来发展方向。第二部分对强化学习理论和多agent强化学习理论进行了简要介绍。在对pursuitgame问题进行初步分析的基础上,针对独立行为学习者,扩展了单agent强化学习算法,提出了基于承诺和约定的多agent协同强化学习方法macrl - cc 。