Multi-agent systems in agentic AI for complex problem-solving

By Muthu Chandra, Chief Data Scientist, Generative AI, Ascendion

In an increasingly interconnected and data-driven world, artificial intelligence (AI) plays a crucial role in solving complex challenges. Among AI paradigms, Multi-Agent Systems (MAS) in Agentic AI stand out as a revolutionary approach to handling intricate, dynamic problems by leveraging distributed intelligence, adaptability, and decentralised decision-making. These systems consist of multiple autonomous agents that interact, collaborate, and optimise outcomes in environments where traditional, monolithic AI models may struggle. This article explores the application of MAS in Agentic AI, focusing on managing complex urban challenges, augmented human decision-making, real-time data sharing, and focused communication and connectivity.

Managing Complex Urban Challenges

Urban environments are evolving rapidly, presenting challenges such as traffic congestion, waste management, energy optimisation, and emergency response. Traditional centralised systems often fall short in addressing these issues due to inefficiencies in resource allocation and delayed response times. MAS ...