为 RL 训练设计奖励函数或排查奖励黑客时使用——决定奖励来自规则、人类偏好还是模型评判,结果奖励还是过程奖励,标量、向量还是生成式诊断,以及如何用路径约束与 RLVP 惩罚违规动作;也用于多轮 Agent 的信用分配、隐藏测试与早停判定设计。触发词:奖励设计、reward hacking、reward seeking、RLVR、RLHF、GRM、ORM、PRM、RLVP、信用分配、隐藏测试、过程奖励、奖励塑形、组内差异。
88%
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tessl scenario generatetessl eval runbojieli/ai-agent-book
dbc046e
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