ASSUME - Agent-based Simulation for Studying and Understanding Market Evolution

A Decision Transformer for solving optimal EV charging problems using offline data.

ICML'2024: Q-value Regularized Transformer for Offline Reinforcement Learning

This project is the source code of paper "Optimizing bidding strategy in electricity market based on graph convolutional neural network and deep reinforcement learning" in Applied Energy 2025.

We perform functional grounding of LLMs' knowledge in BabyAI-Text

Official codebase for Decision Transformer: Reinforcement Learning via Sequence Modeling.

Online Decision Transformer

Multi-Agent Graph Convolutional Reinforcement Learning for Dynamic Electric Vehicle Charging Pricing

Workshop Elia

Transformer-based Multi-Agent Actor-Critic Framework