aqua4freedom

aqua4freedom's Stars

• savinay95n/Reinforcement-learning-Algorithms-and-Dynamic-Programming

  Reinforcement learning Algorithms such as SARSA, Q learning, Actor-Critic Policy Gradient and Value Function Approximation were applied to stabilize an inverted pendulum system and achieve optimal control. So essentially, the concept of Reinforcement Learning Controllers has been established. The Reinforcement Learning Controllers have been compared on the basis of performance and efficiency and they are separately compared with the classical Linear Quadratic Regulator Controller. Each of the RL controller have been integrated with a Swing up controller. A virtual switch toggles between the Swing up controller and the RL controller automatically, based on the value of the angular deviation theta with respect to the vertical plane. My research paper and my undergraduate thesis have been uploaded for reference. All the codes have also been uploaded.

  Language:MATLAB10726

• OpenOCL/OpenOCL

  Open Optimal Control Library for Matlab. Trajectory Optimization and non-linear Model Predictive Control (MPC) toolbox.

  Language:MATLAB37565

• mpopt/mpopt

  A pseudo-spectral collocation based multi-phase Optimal control problem solver

  Language:Python5418

• shungo0222/fixed-point-iteration

  Solve non-linear equations with fixed-point iteration

  Language:C1

• jhlfrfufyfn/mpi-fpi

  Solving linear system with the fixed point iteration method, written in MPI C++

  Language:C++2

• MinhasKamal/AlgorithmImplementations

  Implementation of Elementary Algorithms (infix-prefix-postfix-evaluation-to-longest-common-increasing-sub-sequence-activity-selection-balance-kd-binary-heap-binomial-tree-breath-depth-first-search-max-flow-shortest-path-topological-sort-calculus-derivative-integration-forward-interpolation-simpson-rule-intersecting-area-non-linear-equation-jacobis-gauss-seidal-bisection-false-position-newton-raphson-fixed-point-secant-cigarette-smokers-genetic-huffman-a-a*-star-binary-knuth-morris-pratt-kmp-quick-thread-priority-based-premitive-shortest-job-non-primitive-arithmetic-expression-data-structures-list-node-implementation-one-two-way-linked-stack-string-graph-numerical-methods-equation-solving-solve-process-problem-search-sort-prime-ugly-friend-perfect-fibonacci-factorial-factor-number)

  Language:C++7632

• garrettkatz/rnn-fxpts

  Fixed point solver for recurrent neural networks

  Language:Python32

• wrossmorrow/bneqpri

  Fixed-Point Solver for Bertrand-Nash Equilibrium Pricing Problems

  Language:Python2

• zouchangjie/RL-Nash-Q-learning

  强化学习中纳什Qlearning 实现矩阵博弈

  Language:Python2910

• peterjiawhite/Superhuman_AI_in_multiplayer_poker_-

  该论文主要介绍了美国卡内基梅隆大学团队，在多人德州扑克上的人工智能新思路，即不再简单寻找纳什均衡，而引入悔恨值的概念，自我博弈，并采用蒙特卡洛CFR方法，构建蓝图，该方法通用性强，该团队声称他们的德州扑克蓝图只在两枚CPU运算8天即可得出蓝图，即可以实现实时博弈。现已经有国内团队将其用在了斗地主上面，成效显著。

  Language:Python259

• Zhao-Jichao/MAS_CooperativeClusterMotionControl

  《多智能体系统的协同群集运动控制》-陈杰

  Language:MATLAB348

• colaforced/AgentsMotionSimulation

  多智能体均匀多边形编队、追逐与合围。

  Language:Python452

• sujiongming/starcraftAI

  多智能体即时策略对抗方法与实践 苏炯铭 刘鸿福 陈少飞 项凤涛 编著 科学出版社 2019.11 随书代码

  327

• thesouther/MARL

  多智能体强化学习（MARL）算法复现，包括QMIX，VDN，QTRAN、MAVEN等等

  Language:Python18424

• sumitrj/ConnectedQ-Multi-agent-Reinforcement-Learning-Algorithm

  Modified MDP and Q-Learning Algorithm | Multiagent optimization | Path Planning | Navigation | Reinforcement Learning | Stochastic Systems | Swarm Robotics

  Language:Python688

• atb033/multi_agent_path_planning

  Python implementation of a bunch of multi-robot path-planning algorithms.

  Language:Python1.2k268

• DosepackAIR/MARL-DPP

  Multi Agent Reinforcement Learning for Dense Path Planning

  Language:Python283

• douthwja01/OpenMAS

  OpenMAS is an open source multi-agent simulator based in Matlab for the simulation of decentralized intelligent systems defined by arbitrary behaviours and dynamics.

  Language:MATLAB13350

• GavinPHR/Multi-Agent-Path-Finding

  Anonymous Multi-Agent Path Finding (MAPF) with Conflict-Based Search and Space-Time A*

  Language:Python36456

• qwerty35/swarm_simulator

  Trajectory generation and simulation for multi-agent swarm

  Language:C++12035

• shouyuantianxia/Algorithmic-Game-Theory-Application-on-Multi-agent-Combat-and-Verification-Platform-Design

  本科毕业设计:《多智能体博弈兵棋推演理论与验证平台设计》的源代码附录内容。强化学习算法的实现上参考了周沫凡先生的开源代码https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow

  Language:Python537

• MorvanZhou/Reinforcement-learning-with-tensorflow

  Simple Reinforcement learning tutorials, 莫烦Python 中文AI教学

  Language:Python9k5k

• ZhuLinhai1996/Multi_agent_Reinforcement_Learning

  多代理(Multi agent)强化学习Qlearning算法在多目标探测问题(任务分配+功率优化)中的应用

  Language:Python26

• glong1997/MultiAgentLearning

  多智能体学习库

  Language:HTML161

• openai/maddpg

  Code for the MADDPG algorithm from the paper "Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments"

  Language:Python1.7k496

• MultiAgentLearning/playground

  PlayGround: AI Research into Multi-Agent Learning.

  Language:Python766214

• oxwhirl/pymarl

  Python Multi-Agent Reinforcement Learning framework

  Language:Python1.9k391

• daiweLi/Fast-Combat-Simulation

  A tool that provides fast air combat simulation and display

  Language:C++269

• akako/gamealgorithm-war-simulation

  Language:C#52

• wangwei39120157028/UAVS

  Intelligent UAV path planning simulation system is a software with fine operation control, strong platform integration, omnidirectional model building and application automation. It takes the UAV war between A and B in Zone C as the background. The core function of the system is to plan the UAV route through the simulation platform and verify the output. The data can be imported into the real UAV to make it accurately arrive at any position in the battlefield according to the specified route and support the joint action of multi-person and multi-device formation.

  Language:JavaScript506100