402 Open source projects that are alternatives of or similar to wolpertinger_ddpg

文件 笔和线段的一种划分.py,只需要把k线high，low数据输入，就能自动实现笔，线段，中枢，买卖点，走势类型的划分了。可以把sh.csv 作为输入文件。个人简历见.pdf。时间的力量。有人说择时很困难，有人说选股很容易，有人说统计套利需要的IT配套设施很重要。还有人说系统有不可测原理。众说纷纭。分布式的系统，当你的影响可以被忽略，你才能实现，Jiang主席所谓之，闷声发大财。

CURL: Contrastive Unsupervised Representation Learning for Sample-Efficient Reinforcement Learning

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Summaries of machine learning papers

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Neural Symbolic Machines is a framework to integrate neural networks and symbolic representations using reinforcement learning, with applications in program synthesis and semantic parsing.

A reinforcement learning package for Julia

PyTorch implementation of Trust Region Policy Optimization

Decentralized Reinforcment Learning: Global Decision-Making via Local Economic Transactions (ICML 2020)

PyTorch implementations of Deep Reinforcement Learning algorithms (DQN, DDQN, A2C, VPG, TRPO, PPO, DDPG, TD3, SAC, SAC-AEA)

Minimal implementations of reinforcement learning algorithms by Tensorflow

Minimal Deep Q Learning (DQN & DDQN) implementations in Keras

Implementations from the free course Deep Reinforcement Learning with Tensorflow and PyTorch

AutoPentest-DRL: Automated Penetration Testing Using Deep Reinforcement Learning

Deep-Reinforcement-Learning-for-Dialogue-Generation-in-tensorflow

Solved lab problems, slides and notes of the Deep Reinforcement Learning bootcamp 2017 held at UCBerkeley

Proto-RL: Reinforcement Learning with Prototypical Representations

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"Good Robot! Now Watch This!": Repurposing Reinforcement Learning for Task-to-Task Transfer; and “Good Robot!”: Efficient Reinforcement Learning for Multi-Step Visual Tasks with Sim to Real Transfer

Implementation of the Deep Q-learning algorithm to solve MDPs

Deep Planning Network: Control from pixels by latent planning with learned dynamics

Fitness landscape exploration sandbox for biological sequence design.

Code base for solving Markov Decision Processes and Reinforcement Learning problems using Recurrent Convolutional Neural Networks.

Noisy Networks for Exploration

Deep Reinforcement Learning in Autonomous Driving: the A3C algorithm used to make a car learn to drive in TORCS; Python 3.5, Tensorflow, tensorboard, numpy, gym-torcs, ubuntu, latex

an implementation of CommNet

Deep reinforcement learning using baidu PARL(maze,flappy bird and so on)

For deep RL and the future of AI.

🐵 An AI chess-board-game framework(by many programming languages) implementations.

An OpenAI gym wrapper for CARLA simulator

Reinforcement Learning / AI Bots in Card (Poker) Games - Blackjack, Leduc, Texas, DouDizhu, Mahjong, UNO.

Open-source reinforcement learning environment for autonomous racing.

pytorch implementation of Curiosity-driven Exploration by Self-supervised Prediction

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Basic versions of agents from Spinning Up in Deep RL written in PyTorch

An out-of-the-box GUI tool for offline deep reinforcement learning

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This is a practical resource that makes it easier to learn about and apply Practical Deep Reinforcement Learning (DRL) https://ibrahimsobh.github.io/Practical-DRL/

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Deep Reinforcement Learning Algorithms Implementation in PyTorch

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We have used Deep Reinforcement Learning and Advanced Computer Vision techniques to for the creation of Smart Traffic Signals for Indian Roads. We have created the scripts for using SUMO as our environment for deploying all our RL models.

使用深度强化学习解决视觉跟踪和视觉导航问题