FinRL-X: An AI-Native Modular Infrastructure for Quantitative Trading

portfolio deep-reinforcement-learning sharpe-ratio ddpg stock-trading portfolio-allocation ppo stock-selection a2c-algorithm ensemble-strategy stock-trading-strategy automated-stock-trading finrl finrl-x

• Updated Sep 18, 2026
• Python

Implementing Deep Reinforcement Learning Algorithms in Python for use in the MuJoCo Physics Simulator

python machine-learning reinforcement-learning deep-learning python3 pytorch ddpg sac mujoco deep-deterministic-policy-gradient a2c continuous-action-space soft-actor-critic discrete-action-space a2c-algorithm reinforce-algorithm ant-v3 humanoid-v3 pendulum-v1

• Updated Dec 18, 2021
• TeX

Accepted by AROB 2021. For letting agents in traffic simulation behave more like humans, we propose a unified mechanism for agents learn to decide various accelerations on deep reinforcement learning and generate a traffic flow behaving variously to simulate the real traffic flow.

deep-reinforcement-learning multi-agent-systems multi-agent-reinforcement-learning a2c-algorithm generating-traffic-flows

• Updated May 7, 2021
• GAML

Implementation of RL Algorithms with PyTorch.

reinforcement-learning deep-reinforcement-learning dqn a3c gym-environments prioritized-experience-replay a3c-agent pytorch-implementation dqn-pytorch a2c-pytorch a3c-pytorch a2c-algorithm a2c-agent

• Updated Jan 16, 2023
• Python

Applying A2C-algorithm (Reinforcement Learning) for the control of a DC-motor

reinforcement-learning oop a2c-algorithm discrete-linear-time-invariant

• Updated Feb 2, 2024
• Python

A2C deep reinforcement learning for emergency vehicle prioritization at a real intersection in Kronach, Germany compared with Round Robin and feedback control in SUMO/TraCI.

python reinforcement-learning-algorithms intelligent-transportation-systems traci actor-critic-algorithm traffic-signal-control a2c-algorithm emergency-vehicles sumo-rl

• Updated Nov 5, 2026
• Python

A 股Ai原生训练-交易框架： An AI-Native Modular Infrastructure for A share Quantitative Trading

portfolio deep-reinforcement-learning ddpg ddpg-algorithm a2c-algorithm stock-trading-strategy automated-stock-trading finrl finrl-x automated-stock-analysis stock-trading-platform

• Updated Oct 10, 2026
• Python

A model describing how a car learns to control its acceleration by A2C_TD.

reinforcement-learning minus pytorch rl td gama a2c a2c-algorithm

• Updated Jul 13, 2020
• GAML

Using Imitation Learning for a Wordle agent

behavioral-cloning imitation-learning a2c-algorithm stable-baselines3

• Updated Sep 13, 2024
• Jupyter Notebook

Solving the Atari Breakout environment using Stable Baselines

dqn tensorboard-visualizations trpo ppo pytorch-implementation stable-baselines a2c-algorithm recurrent-ppo qrdqn sb3-contrib

• Updated Oct 25, 2022
• Jupyter Notebook

Implementing some RL algorithms (using PyTorch) on the CartPole environment by OpenAI.

pytorch policy-gradient actor-critic cartpole-v0 boilerplate-code a2c-algorithm

• Updated Aug 24, 2020
• Python

Implementation of the Advantage Actor-Critic (A2C) algorithm for training an agent to balance a pole in the CartPole environment using PyTorch and OpenAI Gym.

reinforcement-learning deep-reinforcement-learning a2c-algorithm

• Updated Oct 13, 2024
• Jupyter Notebook

REINFORCE, Actor-Critic and A2C from scratch on CartPole-v1 against a DQN benchmark - the gap between AC at 370 and A2C at 497 comes down to one baseline subtraction, with AC's critic trained but never used in the actor's gradient

reinforcement-learning pytorch policy-gradient reinforce actor-critic a2c-algorithm

• Updated Sep 6, 2026
• Python

Personal sandbox project for testing reinforcement learning algorithms.

rl a2c-algorithm

• Updated Jul 18, 2023
• Python

This repository explores Reinforcement Learning (RL) through hands-on implementations of key algorithms and environments. It demonstrates how agents learn by interacting with environments, optimizing rewards, and adapting to tasks ranging from Atari games to autonomous driving and custom simulations.

python machine-learning reinforcement-learning tensorboard tensorboard-visualizations a2c-algorithm ppo-algorithm gymnasium-environment

• Updated Aug 28, 2025
• Jupyter Notebook

This repository displays the use of Reinforcement Learning, specifically QLearning, REINFORCE, and Actor Critic (A2C) methods to play CartPole-v0 of OpenAI Gym.

qlearning deep-reinforcement-learning openai-gym reinforce actor-critic a2c-algorithm

• Updated Jan 14, 2021
• Python

Hands-on implementations of Reinforcement Learning algorithms from scratch, progressing from classical methods to deep RL with practical experiments.

reinforcement-learning dqn td-learning monte-carlo-methods ppo advantage-actor-critic actor-critic-methods model-based-reinforcement-learning deep-qlearning-algorithm stochastic-approximation dqn-pytorch model-free-rl sarsa-algorithm q-learning-algorithm a2c-algorithm reinforce-algorithm policy-gradient-algorithm value-function-approximation

• Updated May 1, 2026
• Jupyter Notebook

Advantage Actor-Critic (A2C) reinforcement learning algorithm to detect emerging trends in tweets. The RL agent learns to optimize actions (post, edit, delete) based on engagement metrics such as likes, retweets, and quotes.

algorithm analysis reinforcement-learning-algorithms rl algorithm-design a2c-algorithm nlp-related

• Updated Jan 27, 2025
• Python

Deep Reinforcement Learning with Stable-Baselines3. Benchmarking PPO, A2C, and DQN on Control & Physics Environments

pytorch reinforcementlearning dqn-tensorflow sb3 ppo-pytorch a2c-algorithm

• Updated Oct 27, 2026
• Python

Using the "Advantage Actor Critic(A2C)" Reinforcement Learning method, the 'Agent' is trained to play Atari's Breakout.

reinforcement-learning ai deep-learning deepqlearning a2c-algorithm

• Updated Jan 13, 2022
• Jupyter Notebook