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AWS publishes a complete multi-turn reinforcement-learning pipeline for agents
Focus: Technical AI Engineering
Date: October 23, 2026
Topics: Multi-turn RL, Outcome rewards, SageMaker training
Evidence: Publisher Authored
Availability: Available
Summary: AWS shows a complete multi-turn reinforcement-learning pipeline for teaching GPT-OSS-20B to play Wordle on SageMaker AI. Its reported solve rate rose from 61% to 84% at default reasoning effort and from 15% to 69% at low effort, using outcome rewards, AgentCore execution and iterative rollout training.
Why it matters: You will learn how to frame an agent task, define outcome rewards, collect multi-turn rollouts and compare pretraining with post-training. The cost breakdown and failure modes help teams decide whether a bounded RL experiment is worth running.
Source: Multi-Turn Reinforcement Learning on Amazon SageMaker AI: A hands-on guide