Calculating the reward-rate manifold in the Gaussian-MSE case from Resource-rational reinforcement learning and sensorimotor causal states, and resource-rational maximiners
收藏DataCite Commons2025-10-27 更新2026-04-25 收录
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https://rs.figshare.com/articles/dataset/Calculating_the_reward-rate_manifold_in_the_Gaussian-MSE_case_from_Resource-rational_reinforcement_learning_and_sensorimotor_causal_states_and_resource-rational_maximiners/30454062/1
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资源简介：
Calculates a reward-rate manifold when statistics are Gaussian and the reward function is a squared error. In this case, the generalized Blahut-Arimoto algorithm massively simplifies, and we can use the equations in Appendix D to find Fig 1.
提供机构：
The Royal Society
创建时间：
2025-10-27
