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aws details multi-turn reinforcement learning on amazon sagemaker ai
train agents on sequential tasks using sagemaker ai and amazon bedrock agentcore.
Summary
amazon web services published a hands-on guide for multi-turn reinforcement learning on amazon sagemaker ai. the setup uses amazon bedrock agentcore to host agents and reward functions. the tutorial covers dataset prep, iam roles, group relative policy optimization, and model evaluation.
What changed
- sagemaker ai supports multi-turn reinforcement learning to train models on sequential tasks.
- integration with amazon bedrock agentcore lets you host agents, environments, and reward functions.
- supported base models include amazon nova 2 lite, gpt-oss-20b, gemma 4 31b, and qwen 3.6 27b.
Availability
Available now“Multi-Turn Reinforcement Learning (MTRL) on Amazon SageMaker AI trains models on exactly that signal.”
Founder takeaway
if you are building multi-step agents, read the new guide to test multi-turn reinforcement learning on sagemaker ai.
Source
Researched and drafted with AI from the official sources above, then checked automatically before publishing. Spotted a mistake? Tell us.
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