RideSkill: A Hierarchical Algorithm for Generalized Ride Sharing with LLM-Driven Automatic Evolution

arXiv:2609.02250 · cs.MA, cs.CL, cs.ET, cs.LG · Submitted 2026-09-02 · Read on arXiv

cs.MA, cs.CL, cs.ET, cs.LG

Submitted: 2026-09-02

Updated: 2026-09-23

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Reward Function — 19× in this paper · explained in 2 episodes
• Reinforcement Learning — 13× in this paper · explained in 4 episodes
• Generalization — 10× in this paper · explained in 13 episodes
• Action Space — 6× in this paper · explained in 1 episode
• Benchmark — 6× in this paper · explained in 2 episodes
• Transferability — 6× in this paper · explained in 4 episodes
• Adaptation — 3× in this paper · explained in 1 episode
• Core — 3× in this paper · explained in 2 episodes
• Curse of Dimensionality — 3× in this paper · explained in 6 episodes
• Deep Reinforcement Learning — 3× in this paper · explained in 2 episodes
• Interpretability — 3× in this paper · explained in 15 episodes
• Large Language Models (LLMs) — 3× in this paper · explained in 6 episodes
• Multi-Agent Reinforcement Learning (MARL) — 3× in this paper · explained in 4 episodes
• Cosine Similarity — 2× in this paper · explained in 3 episodes
• Robustness — 2× in this paper · explained in 5 episodes
• Ablation — 1× in this paper · explained in 1 episode
• Additivity — 1× in this paper · explained in 1 episode
• Agent Skills — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Cooperation — 1× in this paper · explained in 2 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• GRPO — 1× in this paper · explained in 6 episodes
• Hallucination — 1× in this paper · explained in 3 episodes
• Hierarchical Framework — 1× in this paper · explained in 2 episodes
• Multi-Agent Markov Decision Process — 1× in this paper
• Non-stationarity — 1× in this paper · explained in 2 episodes
• Objective Function — 1× in this paper · explained in 2 episodes
• Q-learning — 1× in this paper · explained in 3 episodes
• Score Function — 1× in this paper · explained in 4 episodes
• Theoretical Guarantees — 1× in this paper · explained in 2 episodes

Sources

• A Comprehensive Survey on Multi-Agent Cooperative Decision-Making: Scenarios, Approaches, Challenges and Perspectives
• GDPO: Group reward-Decoupled Normalization Policy Optimization for Multi-reward RL Optimization
• ProfiLLM: Utility-Aligned Agentic User Profiling for Industrial Ride-Hailing Dispatch
• Data-Efficient Multi-Agent Spatial Planning with LLMs
• GLM-5: from Vibe Coding to Agentic Engineering
• Large Language Models as Delivery Rider: Generating Instant Food Delivery Riders' Routing Decision with LLM Agent Framework
• One Step is Enough: Multi-Agent Reinforcement Learning based on One-Step Policy Optimization for Order Dispatch on Ride-Sharing Platforms
• RideGym: A Standardized Interface for Real-World Large-Scale Ride-Sharing System
• A Comprehensive Survey on Agent Skills: Taxonomy, Techniques, and Applications

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