Ecom-RLVE: Adaptive Verifiable Environments for E-Commerce Conversational Agents
AI Summary
EcomRLVE-GYM extends the RLVE framework into multi-turn, tool-augmented e-commerce conversational workflows. It features 8 verifiable environments, procedural problem generation, a 12-axis difficulty curriculum, and algorithmically verifiable rewards that assess task completion, efficiency, and hallucination penalties without human annotators or LLM judges.
Key Takeaways
- Extends single-turn RLVE reasoning puzzles to multi-turn agentic e-commerce dialogues.
- Uses a 12-axis difficulty curriculum managed by adaptive scheduling based on agent success rates.
- Employs code-computed rewards evaluating task completion, efficiency, and retrieval hallucinations.
Why it matters
It replaces subjective LLM-as-a-judge evaluations with programmatic verification for e-commerce agents, enabling reliable reinforcement learning of complex, multi-step shopping workflows like cart building and order tracking.
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