True agentic AI is years away - here's why and how we get there

Today's AI agents are a primitive approximation of what agents are meant to be. True agentic AI requires serious advances in reinforcement learning and complex memory.
IEEE

Analogical Learning-Based Few-Shot Class-Incremental Learning

Abstract: FSCIL (Few-shot class-incremental learning) is a prominent research topic in the ML community. It faces two significant challenges: forgetting old class knowledge and overfitting to limited ...
IEEE

A Deep Reinforcement Learning-Based Adaptive Large Neighborhood Search for Capacitated Electric Vehicle Routing Problems

Abstract: The Capacitated Electric Vehicle Routing Problem (CEVRP) poses a novel challenge within the field of vehicle routing optimization, as it requires consideration of both customer service ...
Military.com

Department of Education’s Proposal to Modernize its Definition of Online Distance Learning

The Department of Education revisited proposed changes to asynchronous clock, credit-hour, and subscription-based programs in distance education. In previous years, the Department of Education’s final ...