a2c-algorithm

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

UpdatedMay 7, 2021
GAML

alerch97 /Reinforcement-Learning-controller-for-a-DC-motor

Star3

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

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

UpdatedFeb 2, 2024
Python

kartik2309 /RLPack

Star2

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

UpdatedJan 16, 2023
Python

dv-fenix /ReinforcementLearning

Star1

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

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

UpdatedAug 24, 2020
Python

ZHONGJunjie86 /A2C-TD-single-car-intersection

Star1

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

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

UpdatedJul 13, 2020
GAML

SwamiKannan /Breakout-v0-using-Stable-Baselines

Star1

Solving the Atari Breakout environment using Stable Baselines

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

UpdatedOct 25, 2022
Jupyter Notebook

AnuraagRath /A.I-learns-to-play-Atari-Breakout-ReinforcementLearning

Star1

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

UpdatedJan 13, 2022
Jupyter Notebook

raselmahmud-coder /Emerging-Trend-Detection-using-Reinforcement-Learning-A2C

Star0

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

UpdatedJan 27, 2025
Python

janenotjung-hue /wordle

Star0

Using Imitation Learning for a Wordle agent

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

UpdatedSep 13, 2024
Jupyter Notebook

joaobose /rl-sandbox

Star0

Personal sandbox project for testing reinforcement learning algorithms.

rl a2c-algorithm

UpdatedJul 18, 2023
Python

vikrams169 /Using-RL-in-CartPole-v0

Star0

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

UpdatedJan 14, 2021
Python

ayeenp /deep-rl-a2c-cartpole

Star0

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