GitHub

mll-lab-nu/VAGEN

Kangrui Wang*, Pingyue Zhang*, Zihan Wang*, Yaning Gao*, Linjie Li*, Qineng Wang, Hanyang Chen, Chi Wan, Yiping Lu, Zhengyuan Yang, Lijuan Wang, Ranjay Krishna, Jiajun Wu, Li Fei-Fei, Yejin Choi, ...
North Penn Now

Machine Learning Using Python: A Complete Learning Path With Practical Projects

Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...
GitHub

InftyThink+: Effective and Efficient Infinite-Horizon Reasoning via Reinforcement Learning

Building upon our previous work InftyThink, we introduce InftyThink+, an end-to-end reinforcement learning framework that directly optimizes the complete iterative reasoning trajectory. Building on ...
IEEE

Encoding High-Level Knowledge in Offline Multi-Agent Reinforcement Learning Using Reward Machines

Abstract: Offline reinforcement learning (RL) learns policies from fixed-size datasets without interacting with the environment, while multi-agent reinforcement learning (MARL) faces challenges from ...
IEEE

An Optimal Scheduling Framework for Integrated Energy Systems Using Deep Reinforcement Learning and Deep Learning Prediction Models

Abstract: Model-free deep reinforcement learning has emerged as a promising method for addressing the scheduling challenges in integrated energy systems. However, uncertainty in system states ...