The Chronicle of Higher EducationOpinion

The Solution to AI Cheating Is Within Our Grasp

If we could reliably detect AI use in student papers, that would leave instructors free to decide whether it impedes or ...
The BMJOpinion

Learning through uncertainty: a final year student reflection on placements during prolonged industrial action

Industrial action has become a regular part of NHS life. Since March 2023, repeated junior doctor strikes have affected how ...
The Sector

Play-based learning and early years science: New framework maps how intentional teaching builds scientific literacy

A Charles Sturt University study published in Research in Science Education has mapped a three-stage pathway showing how educator planning, play-based action and reflective practice can work together ...
EurekAlert!

A new AI-based attack framework advances multi-agent reinforcement learning by amplifying vulnerability and bypassing defenses

Researchers have developed a novel framework, termed PDJA (Perception–Decision Joint Attack), that leverages artificial ...
IEEE

A Scalable Reinforcement Learning Framework for Wireless Sensor Networks: Spatiotemporal Cluster-Based Multi-Agent Reinforcement Learning

Abstract: Wireless Sensor Networks face significant scalability challenges when implementing Reinforcement Learning techniques for adaptive decision-making. Traditional approaches utilizing either ...
IEEE

A Deep Reinforcement Learning Framework for Adaptive Resiliency Enhancement in Smart Power Grids

Abstract: This paper addresses the critical challenge of enhancing resiliency in smart power grids against cyber-physical disturbances, including cyber-attacks, system faults, and dynamic load ...
GitHub

Scaling Agentic Reinforcement Learning with a Multi-Turn, Multi-Task Framework

For a minimal example of how to use the environment framework, refer to examples/simple-calculator. For the environment and training data used in our paper, see AgentBench FC. For reproducing the ...
GitHub

Revolutionizing Reinforcement Learning Framework for Diffusion Large Language Models

We propose TraceRL, a trajectory-aware reinforcement learning method for diffusion language models, which demonstrates the best performance among RL approaches for DLMs. We also introduce a ...