Multi-Agent Systems for E-Health and Telemedicine

Multi-Agent Systems for E-Health and Telemedicine

Federico Bergenti (University of Parma, Italy), Agostino Poggi (University of Parma, Italy) and Michele Tomaiuolo (University of Parma, Italy)
Copyright: © 2016 |Pages: 12
DOI: 10.4018/978-1-4666-9978-6.ch053

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Although there are several definitions of agent (see, e.g., Russell & Norvig, 2003; Wooldridge & Jennings, 1995; Genesereth & Ketchpel, 1994), all the definitions agree 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 behavior 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, an agent may also be able to perform complex reasoning at run-time and can also learn and change their behavior over time, to improve its performance. Finally, it is even able to move for one computational node to another, to follow its own user 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, characterized 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. Multi-agent systems can be also considered as abstractions capable of capturing the essence of many software systems at different levels of detail, rather than a single technology supporting the realization of distributed intelligent systems. In particular, agents and multi-agent systems are often considered the highest system level (Newel, 1982; Jennings, 2000) that we can access today and they are meant to provide a truly novel level of abstraction in the analysis, design and implementation of complex software systems (Bergenti & Huhns, 2004).

Key Terms in this Chapter

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.

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.

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.

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.

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.

Negotiation: A process by which a group of agents come to a mutually acceptable agreement on some matter.

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.

Social Service: A service usually provided by a public organization for improving the quality of life of persons.

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