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1-step-sarsa--mario

a2c-lstm-td-single-car-intersection

A model used to identify the usefulness of LSTM with sequential data.

a2c-mc-single-car-intersection

This is a model describing a car runs to goal in limited time with A2C-MC algorithm.

a2c-td-single-car-intersection

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

easy_dppo_multiheads_pytorch

generating-traffic-flows-with-marl

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.

githubtutorial

Githubのチュートリアル資料です。

influential-communication

From paper: Social Influence as Intrinsic Motivation for Multi-Agent Deep Reinforcement Learning. Not the same one.

maddpg_mnist

Use MADDPG to handle the MNIST.

mixed_input_ppo_cnn_lstm_car_navigation

Accepted by AROB 2021. A car-agent navigates in complex traffic conditions by Mixed_Input_PPO_CNN_LSTM model.

modeling-others-as-a-player-mop

Accepted by Proceedings of 24th International Conference on Engineering Applications of Neural Networks (EANN 2023, which will be renamed to Engineering Applications and Advances of Artificial Intelligence, EAAAI 2023)

multiprocessing_per_discrete_sac

ppo_lstm_car_navigation

A car-agent navigates in complex traffic conditions by PPO.

sac_discrete_multiprocessing

td3_sac_ppo_multi_python