Self-adjusting mutation rates let the (1+1) EA optimize the top k bits of BinVal in O(k^{1+ε}) time independent of n for all k in o(n) simultaneously.
Between MDPs and semi-MDPs: a framework for temporal abstraction in reinforcement learning
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Squirrel behaviors supply a comparative template for a hierarchical control model that integrates latent dynamics, episodic memory, observer beliefs, and delayed verification in agentic AI.
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Anytime Analysis on BinVal: Adaptive Parameters Help
Self-adjusting mutation rates let the (1+1) EA optimize the top k bits of BinVal in O(k^{1+ε}) time independent of n for all k in o(n) simultaneously.
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Coupled Control, Structured Memory, and Verifiable Action in Agentic AI (SCRAT -- Stochastic Control with Retrieval and Auditable Trajectories): A Comparative Perspective from Squirrel Locomotion and Scatter-Hoarding
Squirrel behaviors supply a comparative template for a hierarchical control model that integrates latent dynamics, episodic memory, observer beliefs, and delayed verification in agentic AI.