The AI Readiness Paradox: The Agentic Value Gap And The Agentic Operational Model

Legacy metrics—uptime, latency, MTTR—no longer capture operational value in an AI-driven world. Mean time to prevention (MTTP ...
IEEE

The Model-Driven Design Integration Framework (MDDIF): Introduction to an Optimized Product Development Process and a Design for Manufacturing Case Study

Abstract: The complexity of modern system and manufacturing process development often leads to inefficiencies in responsiveness, cost, and quality. This article presents a comprehensive methodology ...
IEEE

Multi-Agent Reinforcement Learning in Non-Cooperative Stochastic Games Using Large Language Models

Abstract: We study the use of large language models (LLMs) to integrate high-level knowledge in stochastic games using reinforcement learning with reward machines to encode non-Markovian and Markovian ...
Frontiers

Joint decision-making for tanker deployment and refueling strategies under berthing time and fuel price uncertainties

This study proposes a robust optimization framework for the joint optimization of tanker deployment and refueling strategies under uncertainties in berthing times and fuel prices. Unlike traditional ...
VentureBeat

Moving past speculation: How deterministic CPUs deliver predictable AI performance

For more than three decades, modern CPUs have relied on speculative execution to keep pipelines full. When it emerged in the 1990s, speculation was hailed as a breakthrough — just as pipelining and ...