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about learning Spring Boot via examples. Spring Boot 教程、技术栈示例代码，快速简单上手教程。
spring boot 实践学习案例，是 spring boot 初学者及核心技术巩固的最佳实践。
🔥 官方推荐 🔥 RuoYi-Vue 全新 Pro 版本，优化重构所有功能。基于 Spring Boot + MyBatis Plus + Vue & Element 实现的后台管理系统 + 微信小程序，支持 RBAC 动态权限、数据权限、SaaS 多租户、Flowable 工作流、三方登录、支付、短信、商城、CRM、ERP、AI 大模型等功能。你的 ⭐️ Star ⭐️，是作者生发的动力！
一款基于Netty+Zookeeper+Spring实现的轻量级Java RPC框架。提供服务注册，发现，负载均衡，支持API调用，Spring集成和Spring Boot starter使用。是一个学习RPC工作原理的良好示例。
每天都在进步，每周都在总结，Java架构师成长之路。目前已经完成：MongoDB，Netty，Nginx，MySQL，Java，Redis，Shiro，Solr，SpringBoot，SpringData，SSO，Mybatis，Kotlin，还在持续更新中
Springboot-Notebook 一个以 springboot 为基础开发框架， 整合 Redis 、Mysql 、 Rabbitmq 、ES 、MongoDB、sharding-jdbc 分库分表、zookeeper 、web人脸识别 、实时消息推送 、SQL优化、注册中心 、数据脱敏 等互联网主流技术， 文章图解理论配合实战案例，实现开发中常见功能点的综合项目。 本着拿来即用的原则…
Combining Backpropagation with Equilibrium Propagation to improve an Actor-Critic Reinforcement Learning framework
JAX Implementation of Proximal Policy Optimisation Algorithm
Sampling based Model Predictive Control package for Model-Based RL research
Safe control of unknown dynamic systems with reinforcement learning and model predictive control
Combining Reinforcement Learning with Model Predictive Control for On-Ramp Merging
This repository contains the code for our paper on Dynamic Mirror Descent based MPC for Model-Free RL
Author's Pytorch implementation of ICLR2023 paper Behavior Proximal Policy Optimization (BPPO).
Repository of the work: Improving robot navigation in crowded environments using intrinsic rewards (ICRA 2023)
Implementation of our NeurIPS 2021 paper "A Bi-Level Framework for Learning to Solve Combinatorial Optimization on Graphs".
PyTorch implementation of GAIL and AIRL based on PPO.
Pytorch based library containing reinforcement learning agents with forward models and intrinsic motivation modules
Master's thesis on model-based intrinsically motivated reinforcement learning in robotic control
Proximal Policy Optimization(PPO) with Intrinsic Curiosity Module(ICM) on Pyramid env, Unity ML
PyTorch implements multi-agent reinforcement learning algorithms, including QMIX, Independent PPO, Centralized PPO, Grid Wise Control, Grid Wise Control+PPO, Grid Wise Control+DDPG.
Proximal Policy Optimization(PPO) with Intrinsic Curiosity Module(ICM)
The source code for the blog post The 37 Implementation Details of Proximal Policy Optimization
Use DQN to boost MPC computation for dynamic obstacle avoidance.
Clean baseline implementation of PPO using an episodic TransformerXL memory
Obstacle avoidance strategy using a laser sensor to avoid dynamic obstacles (Testing several deep rl algorithms)
This repository contains the implementation of reinforcement learning algorithms like PPO and A2C, to solve the problem: Dynamic Obstacle Avoidance in Generalized Environment.