Abstract
Multi-agent systems have been importantly contributing to the development of the theory and the practice of complex distributed systems and, in particular, they have shown the potential to meet critical needs in high-speed, mission-critical, content-rich, and distributed information applications where mutual interdependencies, dynamic environments, uncertainty, and sophisticated control play a role. Multi-agent systems can be considered a suitable technology for the realization of applications for providing e-health services where the use of loosely coupled and heterogeneous components, the dynamic and distributed management of data, and the remote collaboration among users are often the most relevant requirements.
Top2. Background
While a number of definitions have been proposed for identifying a “software agent” and a “multi-agent system” (see, e.g., Russell & Norvig, 2003; Wooldridge & Jennings, 1995; Genesereth & Ketchpel, 1994), there is not a single one which researchers generally agree on. Nevertheless, there is a common understanding that an agent is essentially an autonomous software entity that should at least be designed to operate continuously in dynamic and uncertain environments, reacting to events while showing an intelligent behaviour to pursue its own objectives. An agent usually provides interoperable interfaces for interacting with other agents, either concurrently or cooperatively, exchanging messages formulated according to some syntax, semantics, and pragmatics. Since an agent behaves proactively, it requires some degree of trust by its user, and it can receive delegations from either human users or other agents in the form of required actions or desired goals, matched with permissions to access necessary resources. Additionally, some agents may also be able to perform complex reasoning at run-time and also learn and change their behaviour over time, to improve their performances. Mobile agents are even able to move for one computational node to another, to follow their own users or to exploit some local resource more efficiently. Agent-based systems are often realized by loosely coupling various agents, i.e. autonomous software entities, thus modelling a proper multi-agent system, characterised by a higher level of modularity and a richer descriptive model, if compared with a solitary agent working within its environment—either with the presence of users or not.
Key Terms in this Chapter
Software Agent: A software agent is a computer program that is situated in some environment and capable of autonomous action in order to meet its design objectives.
Coordination: Coordination is a process in which a group of agents engages in order to ensure that each of them acts in a coherent manner.
Negotiation: A process by which a group of agents come to a mutually acceptable agreement on some matter.
Organizational Structuring: A process for defining the organizational structure of a multi-agent system, i.e., the information, communication, and control relationships among the agents of the system.
Multi-Agent Planning: A process that can involve agents plan for a common goal, agents coordinating the plan of others, or agents refining their own plans while negotiating over tasks or resources.
Multi-Agent System: A Multi-Agent System (MAS) is a loosely coupled network of software agents that interact to solve problems that are beyond the individual capacities or knowledge of each software agent.
Contracting: A process where agents can assume the role of manager and contractor and where managers try to assign tasks to the most appropriate contractors.