Abstract: This paper investigates the problem of tracking morphologically similar targets for nonlinear systems and proposes an adaptive-gain reinforcement iterative learning control (AG-RILC) scheme.

Abstract: This paper studies the iterative learning control with prescribed performance (namely, prescribed iterative learning control, P-ILC) for switched systems, aiming to plan the dynamic and ...

Adult learning theory is a manual for classroom diplomacy, not a map of the mind. Walk into any corporate leadership retreat or faculty development workshop, and you will encounter a familiar set of ...

A production-grade machine learning system that predicts whether a telecom customer will churn. Built as an end-to-end MLOps project covering the full lifecycle from raw data to a monitored, ...

Anthropic’s new Economic Index report, published on January 15, 2026, provides updated data on translation-related usage of its Claude models, alongside signals around how translators interact with AI ...

Many nonprofits in low- and middle-income countries face a critical mismatch: urgent social problems demand rapid program iteration, yet organizations often wait years for externally-produced ...

Lior Weinstein is a fractional CTO/CRO and founder of CTOx, coaching tech executives to multiply their impact as fractional leaders. Two CEOs face the same market opportunity. Both see the potential, ...

AI can be added to legacy motion control systems in three phases with minimal disruption: data collection via edge gateways, non-interfering anomaly detection and supervisory control integration.

In this tutorial, we build an advanced Agentic Retrieval-Augmented Generation (RAG) system that goes beyond simple question answering. We design it to intelligently route queries to the right ...