Special Issue “Multi-Agent Systems”: Editorial

Abstract

Multi-agent systems (MAS) are built around the central notions of agents, interaction, and environment. Agents are autonomous computational entities able to pro-actively pursue goals, and re-actively adapt to environment change. In doing so, they leverage on their social and situated capabilities: interacting with peers, and perceiving/acting on the environment. The relevance of MAS is steadily growing as they are extensively and increasingly used to model, simulate, and build heterogeneous systems across many different application scenarios and business domains, ranging from logistics to social sciences, from robotics to supply chain, and more. The reason behind such a widespread and diverse adoption lies in MAS great expressive power in modeling and actually supporting operational execution of a variety of systems demanding decentralized computations, reasoning skills, and adaptiveness to change, which are a perfect fit for MAS central notions introduced above. This special issue gathers 11 contributions sampling the many diverse advancements that are currently ongoing in the MAS field.

Agent‐Oriented Software Engineering Methodologies: Analysis and Future Directions

“…Presently, computer system applications are becoming more and more complex. In this respect, the benefits associated with using MAS in all types of software engineering programming require strong support for engineering complex open systems that emphasize the social aspects of an agent system [55]. Among the most important features to add AO paradigms in software engineering is the ability to develop and implement complex systems [56].…”

Agent-Based Dynamic Simulation for Supply Chain Management of LNG Import Terminals

“…6 Further, the flexibility offered by ABMs has opened up new horizons in modeling complex and intelligent systems. 7 Given these benefits offered by ABMs, we use them to emulate the LNG SC. In this paper, we develop an agent-based dynamic simulation model for an LNG importer's integrated SC and demonstrate its ability to encapsulate complex dynamics and associated decision-making.…”

“…Simulations based on agent-based models have been found to replicate real-world behavior closely . Further, the flexibility offered by ABMs has opened up new horizons in modeling complex and intelligent systems . Given these benefits offered by ABMs, we use them to emulate the LNG SC.…”