BlockBlast reimplementation + RL agents (DQN, PPO, PPO+Action Masking, DQN+Action Masking, Random)
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Updated
Apr 25, 2025 - Python
BlockBlast reimplementation + RL agents (DQN, PPO, PPO+Action Masking, DQN+Action Masking, Random)
This repository contains code for the paper "Multi-agent reinforcement learning with action masking for uav-enabled mobile communications" which has been accepted for publishing in IEEE Transactions on Machine Learning in Communications and Networking.
Source code of “Agile Reinforcement Learning for Real-Time Task Scheduling in Edge Computing” (CAIAC 2025)
My MSc project on applying, tuning and modifying the PPO and A2C algorithms to Pettingzoo MARL library two player poker game
Code for hierarchical signal coordination using hybrid model-based and RL approach.
Bot Pokémon Gen 1 (Random Battle Showdown) entraîné en RL avec MaskablePPO, imitation + curriculum + self-play ; suivi MLflow.
Neuro-symbolic RL agent that learns to pentest networks it has never seen — GPT-4o compiles CVE preconditions into a Z3 action mask over a GraphSAGE PPO policy. Zero-shot attack-graph transfer, negatives disclosed.
숫자 퍼즐 ‘사과 게임’을 pygame으로 구현하고, Gymnasium 환경에서 PPO·DQN·Monte Carlo 에이전트를 학습·실행하며 사람 vs PPO 대결까지 지원합니다.
Board game agent learning strategy through PPO self-play over 5,000 episodes. 3-layer network (256->128->64), action masking for valid moves. Achieves 78% win rate vs random opponent, up from 56% at training start. 100% valid move rate maintained throughout.
RL agent learns to generate drug-like molecules token-by-token in SMILES notation using PPO/SAC with optional action masking, LSTM policy, and RDKit-based multi-objective scoring (QED, SA score, LogP, Tanimoto similarity).
Safe reinforcement learning with PPO-based action masking and penalty methods in MiniGrid Lava environments.
Unofficial Stable-Baselines3 extension package with MaskableRecurrentPPO.
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