LEARNING
潜在记忆宫殿:作为自回归变分推理的控制推理
Chuning Zhu, Eva Xu, Jose Barreiros, Krishnan Srinivasan, Paarth Shah, Abhishek Gupta
- 发表年份
- 2026
- 访问权限
- 开放获取
摘要
本文提出潜在记忆宫殿(LMP)方法,将控制策略的推理建模为自回归潜在空间中的变分推理,通过强化学习优化其变分下界。该方法在仿真和真实环境中表现出色,并实现了可解释的自适应测试时计算分配。
关键词
autoregressive variational inferencelatent space reasoningcontinuous controlreinforcement learningadaptive computation
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