Author Description

Multi-agent systems powered by large language models (LLMs) emerge as a groundbreaking approach to building more capable, autonomous, and collaborative AI. Unlike traditional single-agent models, multi-agent LLM systems coordinate multiple specialized agents, each with unique roles and capabilities, to solve complex tasks more efficiently and intelligently. Recent advancements in this field have driven innovations across domains such as robotics, software development, scientific research, and strategic decision-making. These systems represent a shift toward the next-generation AI that is more powerful, adaptable, interactive, and aligned with human goals. Advancements in Multi-Agent Large Language Model Systems for Next-Generation AI explores LLMs and multi-agent systems to generate sophisticated AI models. It examines these models as powerful tools to solve complicated problems in intelligent technology applications. This book covers topics such as data science, quantum computing, and sustainability, and is a useful resource for business owners, computer engineering, academicians, researchers, and scientists.