Open source software
CityFlow
A multi-agent reinforcement-learning environment for large-scale city traffic scenarios, orders of magnitude faster than SUMO for training RL-based signal control.
Honor of Kings Arena
A competitive multi-agent reinforcement-learning environment built on Tencent's Honor of Kings MOBA game, designed to benchmark generalization across heroes, lineups, and opponents.
Instructional Agents
A multi-agent LLM system that reduces teaching-faculty workload by automating instructional design — lecture plans, slides, quizzes, and course material generation.
IntelliLight
A reinforcement-learning approach for intelligent traffic-light control — one of the earliest deep-RL methods for adaptive signal control on real-world road networks.
RL_Signals
A curated hub of papers, datasets, simulators, and tutorials covering reinforcement learning for traffic signal control — the go-to reading list for newcomers to the area.
LibSignal
A unified open library for traffic signal control with reproducible RL baselines across simulators (CityFlow, SUMO), standardized benchmarks, and cross-simulator evaluation.
PyDimension
Dimensionless learning — data-driven discovery of dimensionless numbers and scaling laws from scarce experimental measurements, combining physics priors with sparse regression.
PromptGAT
Prompt-to-Transfer: closing the sim-to-real gap for traffic signal control by conditioning a grounded action transformer on natural-language prompts.
CoMAL
Collaborative Multi-Agent Large Language Models for mixed-autonomy traffic — coordinating CAVs and human-driven vehicles via LLM-based negotiation and planning.
CityFlowER
An efficient and realistic traffic simulator with embedded machine-learning vehicle-behavior models, bridging the gap between rule-based speed and data-driven realism.