登录
首页 » matlab » reinforcement-learning-master

reinforcement-learning-master

于 2020-05-01 发布
0 192
下载积分: 1 下载次数: 5

代码说明:

说明:  在障碍物环境下的基于强化学习的单智能体与多智能体路径规划算法(Single agent and multi-agent path planning algorithm based on reinforcement learning in obstacle environment)

文件列表:

reinforcement-learning-master, 0 , 2018-06-01
reinforcement-learning-master\.gitattributes, 66 , 2018-06-01
reinforcement-learning-master\MAL, 0 , 2018-06-01
reinforcement-learning-master\MAL\01 MA Centralized-Q, 0 , 2018-06-01
reinforcement-learning-master\MAL\01 MA Centralized-Q\LFAEstimator.m, 807 , 2018-06-01
reinforcement-learning-master\MAL\01 MA Centralized-Q\MAEnvironment.m, 7602 , 2018-06-01
reinforcement-learning-master\MAL\01 MA Centralized-Q\macq.m, 3115 , 2018-06-01
reinforcement-learning-master\MAL\01 MA Centralized-Q\maq_iterationCount.mat, 5988 , 2018-06-01
reinforcement-learning-master\MAL\01 MA Centralized-Q\maq_reward.mat, 5987 , 2018-06-01
reinforcement-learning-master\MAL\01 MA Centralized-Q\weights.mat, 1487 , 2018-06-01
reinforcement-learning-master\MAL\02 MA Hysteretic-Q, 0 , 2018-06-01
reinforcement-learning-master\MAL\02 MA Hysteretic-Q\LFAEstimator.m, 1003 , 2018-06-01
reinforcement-learning-master\MAL\02 MA Hysteretic-Q\MAEnvironment.m, 7775 , 2018-06-01
reinforcement-learning-master\MAL\02 MA Hysteretic-Q\a1_weights.mat, 536 , 2018-06-01
reinforcement-learning-master\MAL\02 MA Hysteretic-Q\a2_weights.mat, 535 , 2018-06-01
reinforcement-learning-master\MAL\02 MA Hysteretic-Q\mahq.m, 3720 , 2018-06-01
reinforcement-learning-master\MAL\02 MA Hysteretic-Q\maq_iterationCount.mat, 5739 , 2018-06-01
reinforcement-learning-master\MAL\02 MA Hysteretic-Q\maq_reward.mat, 5760 , 2018-06-01
reinforcement-learning-master\MAL\03 MAPG, 0 , 2018-06-01
reinforcement-learning-master\MAL\03 MAPG\MAEnvironment.m, 7775 , 2018-06-01
reinforcement-learning-master\MAL\03 MAPG\PolicyEstimator.m, 1122 , 2018-06-01
reinforcement-learning-master\MAL\03 MAPG\ValueEstimator.m, 844 , 2018-06-01
reinforcement-learning-master\MAL\03 MAPG\agent1_policy_weights.mat, 536 , 2018-06-01
reinforcement-learning-master\MAL\03 MAPG\agent2_policy_weights.mat, 537 , 2018-06-01
reinforcement-learning-master\MAL\03 MAPG\mapg.m, 3389 , 2018-06-01
reinforcement-learning-master\MAL\03 MAPG\mapg_iterationCount.mat, 3556 , 2018-06-01
reinforcement-learning-master\MAL\03 MAPG\mapg_reward.mat, 3608 , 2018-06-01
reinforcement-learning-master\MAL\03 MAPG\value_weights.mat, 216 , 2018-06-01
reinforcement-learning-master\MAL\Basic Functions, 0 , 2018-06-01
reinforcement-learning-master\MAL\Basic Functions\clcAngle.m, 463 , 2018-06-01
reinforcement-learning-master\MAL\Basic Functions\compare_fig.m, 1759 , 2018-06-01
reinforcement-learning-master\MAL\Basic Functions\ds2nfu.m, 2946 , 2018-06-01
reinforcement-learning-master\MAL\Basic Functions\make_epsilon_policy.m, 334 , 2018-06-01
reinforcement-learning-master\MAL\Basic Functions\make_greedy_policy.m, 277 , 2018-06-01
reinforcement-learning-master\MAL\Basic Functions\make_random_policy.m, 92 , 2018-06-01
reinforcement-learning-master\MAL\Basic Functions\q_value_or_policy2fig.m, 3218 , 2018-06-01
reinforcement-learning-master\MAL\Basic Functions\sigmoid.m, 51 , 2018-06-01
reinforcement-learning-master\README.md, 759 , 2018-06-01
reinforcement-learning-master\SAL, 0 , 2018-06-01
reinforcement-learning-master\SAL\01 DP, 0 , 2018-06-01
reinforcement-learning-master\SAL\01 DP\PE.m, 522 , 2018-06-01
reinforcement-learning-master\SAL\01 DP\PE_V.mat, 5034 , 2018-06-01
reinforcement-learning-master\SAL\01 DP\PI.m, 2383 , 2018-06-01
reinforcement-learning-master\SAL\01 DP\PI_P.mat, 696 , 2018-06-01
reinforcement-learning-master\SAL\01 DP\PI_P.svg, 56294 , 2018-06-01
reinforcement-learning-master\SAL\01 DP\PI_V.mat, 6922 , 2018-06-01
reinforcement-learning-master\SAL\01 DP\PI_simulationTime.mat, 192 , 2018-06-01
reinforcement-learning-master\SAL\01 DP\VI.m, 2456 , 2018-06-01
reinforcement-learning-master\SAL\01 DP\VI_P.mat, 361 , 2018-06-01
reinforcement-learning-master\SAL\01 DP\VI_P.svg, 54344 , 2018-06-01
reinforcement-learning-master\SAL\01 DP\VI_Q.mat, 25500 , 2018-06-01
reinforcement-learning-master\SAL\01 DP\VI_Q.svg, 56806 , 2018-06-01
reinforcement-learning-master\SAL\01 DP\VI_V.mat, 4881 , 2018-06-01
reinforcement-learning-master\SAL\01 DP\VI_simulationTime.mat, 192 , 2018-06-01
reinforcement-learning-master\SAL\01 DP\Values.xlsx, 26566 , 2018-06-01
reinforcement-learning-master\SAL\01 DP\policy_evaluation.m, 781 , 2018-06-01
reinforcement-learning-master\SAL\02 MC, 0 , 2018-06-01
reinforcement-learning-master\SAL\02 MC\offpmc.m, 4645 , 2018-06-01
reinforcement-learning-master\SAL\02 MC\offpmc_c.mat, 20341 , 2018-06-01
reinforcement-learning-master\SAL\02 MC\offpmc_iterationCount.mat, 109202 , 2018-06-01
reinforcement-learning-master\SAL\02 MC\offpmc_policy.mat, 1317 , 2018-06-01
reinforcement-learning-master\SAL\02 MC\offpmc_q.mat, 20092 , 2018-06-01
reinforcement-learning-master\SAL\02 MC\offpmc_reward.mat, 1885 , 2018-06-01
reinforcement-learning-master\SAL\02 MC\onpmc.m, 4255 , 2018-06-01
reinforcement-learning-master\SAL\02 MC\onpmc_iterationCount.mat, 78957 , 2018-06-01
reinforcement-learning-master\SAL\02 MC\onpmc_policy.mat, 2485 , 2018-06-01
reinforcement-learning-master\SAL\02 MC\onpmc_q.mat, 27688 , 2018-06-01
reinforcement-learning-master\SAL\02 MC\onpmc_returns.mat, 36066 , 2018-06-01
reinforcement-learning-master\SAL\02 MC\onpmc_reward.mat, 1015 , 2018-06-01
reinforcement-learning-master\SAL\03 TD, 0 , 2018-06-01
reinforcement-learning-master\SAL\03 TD\qLearning.m, 2976 , 2018-06-01
reinforcement-learning-master\SAL\03 TD\qLearning_iterationCount.mat, 90583 , 2018-06-01
reinforcement-learning-master\SAL\03 TD\qLearning_q.mat, 27502 , 2018-06-01
reinforcement-learning-master\SAL\03 TD\qLearning_reward.mat, 5288 , 2018-06-01
reinforcement-learning-master\SAL\03 TD\sarsa.m, 3327 , 2018-06-01
reinforcement-learning-master\SAL\03 TD\sarsa_iterationCount.mat, 91987 , 2018-06-01
reinforcement-learning-master\SAL\03 TD\sarsa_q.mat, 27541 , 2018-06-01
reinforcement-learning-master\SAL\03 TD\sarsa_reward.mat, 1559 , 2018-06-01
reinforcement-learning-master\SAL\04 LFA, 0 , 2018-06-01
reinforcement-learning-master\SAL\04 LFA\LFAEstimator.m, 807 , 2018-06-01
reinforcement-learning-master\SAL\04 LFA\linear_function_approximation.m, 3454 , 2018-06-01
reinforcement-learning-master\SAL\04 LFA\onp_lfa_iterationCount.mat, 125625 , 2018-06-01
reinforcement-learning-master\SAL\04 LFA\onp_lfa_reward.mat, 1702 , 2018-06-01
reinforcement-learning-master\SAL\04 LFA\onp_lfa_weights.mat, 328 , 2018-06-01
reinforcement-learning-master\SAL\05 DQN, 0 , 2018-06-01
reinforcement-learning-master\SAL\05 DQN\DQN.m, 4158 , 2018-06-01
reinforcement-learning-master\SAL\05 DQN\DQNEstimator.m, 3079 , 2018-06-01
reinforcement-learning-master\SAL\05 DQN\DQN_iterationCount.mat, 23638 , 2018-06-01
reinforcement-learning-master\SAL\05 DQN\DQN_reward.mat, 2976 , 2018-06-01
reinforcement-learning-master\SAL\05 DQN\DQN_simulationTime.mat, 241 , 2018-06-01
reinforcement-learning-master\SAL\05 DQN\DQN_weights.mat, 844598 , 2018-06-01
reinforcement-learning-master\SAL\05 DQN\dqn_rwd.png, 9910 , 2018-06-01
reinforcement-learning-master\SAL\06 LPG, 0 , 2018-06-01
reinforcement-learning-master\SAL\06 LPG\PolicyEstimator.m, 1135 , 2018-06-01
reinforcement-learning-master\SAL\06 LPG\ValueEstimator.m, 844 , 2018-06-01
reinforcement-learning-master\SAL\06 LPG\pg_iterationCount.mat, 103307 , 2018-06-01
reinforcement-learning-master\SAL\06 LPG\pg_reward.mat, 2130 , 2018-06-01
reinforcement-learning-master\SAL\06 LPG\policy_gradient.m, 3366 , 2018-06-01
reinforcement-learning-master\SAL\06 LPG\policy_weights.mat, 330 , 2018-06-01
reinforcement-learning-master\SAL\06 LPG\value_weights.mat, 211 , 2018-06-01

下载说明:请别用迅雷下载,失败请重下,重下不扣分!

发表评论

0 个回复

  • bv_cvxbook
    CVX的使用方法 它是一种很有用的MATLAB设计工具(CVX to use it is a very useful design tool MATLAB)
    2010-07-12 11:54:52下载
    积分:1
  • list
    Program to implement a list data structure in C++ (partial) With debug output for poor-man s animation
    2007-11-10 15:25:40下载
    积分:1
  • simulinkthermal
    介绍了MATLAB软件的SIMULIK的使用方法,阐述了MATLAB软件在火电厂自动控制系统调整中的应用(on MATLAB software SIMULIK of use, MATLAB software described in the thermal power plant control system adjustment of)
    2006-11-28 17:34:15下载
    积分:1
  • kiuseng
    利用matlab GUI实现的串口编程例子,对于初学者具有参考意义,小波包分析提取振动信号中的特征频率。( Use serial programming examples matlab GUI implementation, For beginners with a reference value, Wavelet packet analysis to extract vibration signal characteristic frequency.)
    2016-04-26 18:07:09下载
    积分:1
  • multi_port
    基于MATLAB的multi_port详解,主要解决的是multi_port的问题()
    2008-04-06 22:02:16下载
    积分:1
  • invertersvpwm
    inverter space vector pwm
    2010-03-05 12:38:35下载
    积分:1
  • waveaenergy
    此程序为小波包变换结合和能量谱分析提取特征频率(This procedure for the analysis of wavelet packet transform and energy spectrum feature extraction of frequency combination)
    2015-04-15 17:09:05下载
    积分:1
  • 115
    提取目标位置参考点和目标匹配模板;使用基于区域特征的运动目标跟踪算法获取目标位置(像素) (Extraction of target location and target reference points match template use region-based feature tracking algorithm for moving object target location (pixels))
    2010-06-16 08:42:18下载
    积分:1
  • licenserecognition
    说明:  对数字车牌的识别,详细揭示了过程,并提供了实验报告。(Digital license plate recognition, in detail reveals the process and provide an experimental report.)
    2010-03-29 10:57:35下载
    积分:1
  • Rayleigh
    设计信号传输的经典Rayleigh信道模型 由纯多径信号分量(没有直射分量)组成的接收信号包络服从 Rayleigh分布。 (Rayleigh signal model)
    2014-08-11 10:51:01下载
    积分:1
  • 696516资源总数
  • 106914会员总数
  • 0今日下载