#stability3 articles

3 articles

AIBullisharXiv – CS AI · 6h ago1

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Reinforcement Learning for Control with Probabilistic Stability Guarantee: A Finite-Sample Approach

Researchers have developed L-REINFORCE, a novel reinforcement learning algorithm that provides probabilistic stability guarantees for control systems using finite data samples. The approach bridges reinforcement learning and control theory by extending classical REINFORCE algorithms with Lyapunov stability methods, demonstrating superior performance in Cartpole simulations.

AIBullisharXiv – CS AI · 6h ago0

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CHLU: The Causal Hamiltonian Learning Unit as a Symplectic Primitive for Deep Learning

Researchers propose the Causal Hamiltonian Learning Unit (CHLU), a physics-based deep learning primitive that addresses stability issues in temporal dynamics models. The CHLU uses symplectic integration and Hamiltonian structure to maintain infinite-horizon stability while preserving information, potentially solving the memory-stability trade-off in neural networks.

AINeutralarXiv – CS AI · 6h ago0

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Decoupling Stability and Plasticity for Multi-Modal Test-Time Adaptation

Researchers propose DASP (Decoupling Adaptation for Stability and Plasticity), a novel framework for adapting multi-modal AI models to changing test environments. The method addresses key challenges of negative transfer and catastrophic forgetting by using asymmetric adaptation strategies that treat biased and unbiased modalities differently.