info-driven-policy-optimization-agents

Optimize multi-turn agent policies by measuring turn-level information gain via counterfactual reasoning. Provide dense reward signals identifying which clarifying questions and observations improve the agent's decision distribution, then adaptively blend information rewards with outcome rewards.

Independent GitHub snapshot · Automated classification · Original documentation governs