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Found 5 papers, 2 papers with code
AlignIQL: Policy Alignment in Implicit Q-Learning through Constrained Optimization
IDQL reinterprets IQL as an actor-critic method and gets weights of implicit policy, however, this weight only holds for the optimal value function.
Offline Goal-Conditioned Reinforcement Learning for Safety-Critical Tasks with Recovery Policy
Offline goal-conditioned reinforcement learning (GCRL) aims at solving goal-reaching tasks with sparse rewards from an offline dataset.
DiffCPS: Diffusion Model based Constrained Policy Search for Offline Reinforcement Learning
Constrained policy search (CPS) is a fundamental problem in offline reinforcement learning, which is generally solved by advantage weighted regression (AWR).
Data-Driven Robust Control for Discrete Linear Time-Invariant Systems: A Descriptor System Approach
Given the recent surge of interest in data-driven control, this paper proposes a two-step method to study robust data-driven control for a parameter-unknown linear time-invariant (LTI) system that is affected by energy-bounded noises.
Data-Driven Controllability Analysis and Stabilization for Linear Descriptor Systems
For a parameter-unknown linear descriptor system, this paper proposes data-driven methods to testify the system's type and controllability and then to stabilize it.
