A conversation with the assistant provost for teaching and learning and director, Center for the Enhancement of Learning and Teaching at the University of Kentucky.

Wellness is a multi-trillion pound industry which continues to grow - and this year is less about maxing out, more about ...

Abstract: Reinforcement learning (RL) has emerged as a key approach for training agents in complex and uncertain environments. Incorporating statistical inference in RL algorithms is essential for ...

Abstract: This paper compares the control strategies of three reinforcement learning algorithms, namely, Q-learning, SARSA, and Double Q-learning for the CartPole-V1 simulation environment using the ...

1 School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, USA. 2 Department of Electrical and Computer Engineering, Duke University, Durham, NC, USA. As cloud ...

Unmanned surface vehicles (USVs) nowadays have been widely used in ocean observation missions, helping researchers to monitor climate change, collect environmental data, and observe marine ecosystem ...

The Recentive decision exemplifies the Federal Circuit’s skepticism toward claims that dress up longstanding business problems in machine-learning garb, while the USPTO’s examples confirm that ...

This important study uses reinforcement learning to study how turbulent odor stimuli should be processed to yield successful navigation. The authors find that there is an optimal memory length over ...

A high-fidelity Python implementation of the Q-learning oligopoly simulation from Calvano et al. (2020). This project provides a complete, tested, and extensible reproduction of the seminal study ...

Hierarchical Reinforcement Learning in the Taxi-v3 environment using SMDP Q-Learning and Intra-Option Q-Learning to evaluate the impact of option design on performance, sample efficiency, and policy ...