IEEE

Warfarin Dose Management Using Offline Deep Reinforcement Learning

Abstract: Warfarin is a commonly prescribed anticoagulant with a narrow therapeutic window, which requires frequent and specialized monitoring. This work aims to develop standardized optimal warfarin ...
GitHub

meta-reinforcement-learning

Unified meta-reinforcement learning benchmark for fast adaptation with State Space Models (SSM), test-time improvement, and modular policy orchestration. Includes automated training, evaluation, ...
C&EN

dpdata: A Scalable Python Toolkit for Atomistic Machine Learning Data Sets

School of Artificial Intelligence and Data Science, Unversity of Science and Technology of China, Hefei 230026, P. R. China Suzhou Institute for Advanced Research, University of Science and Technology ...
marktechpost

Weak-for-Strong (W4S): A Novel Reinforcement Learning Algorithm that Trains a weak Meta Agent to Design Agentic Workflows with Stronger LLMs

W4S operates in turns. The state contains task instructions, the current workflow program, and feedback from prior executions. An action has 2 components, an analysis of what to change, and new Python ...
GitHub

Demystifying Reinforcement Learning in Agentic Reasoning

An overview of our research on agentic RL. In this work, we systematically investigate three dimensions of agentic RL: data, algorithms, and reasoning modes. Our findings reveal: Real end-to-end ...
IEEE

Smart Maze Solver Using Reinforcement Learning

Abstract: Smart Maze solver Using Reinforcement Learning (RL) aims to develop an agent capable of solving a maze-environment by using its learning in an RL algorithm specifically, Q-learning Algorithm ...