Multi-Agent Systems and Social Networks

Multi-Agent Systems and Social Networks

Enrico Franchi (DII, Università di Parma, Italy) and Agostino Poggi (DII, Università di Parma, Italy)
DOI: 10.4018/978-1-61350-168-9.ch005


The evolution of multi-agent systems theories and technologies has important relationships with the evolution of social networks. In fact, the study of social structures such as organizations and coalitions is one of the most important topics of the research on multi-agent systems; while such a study can take advantage of the works on social network analysis, multi-agent systems can be used both for simulating the evolution of social networks and for providing technological supports for the realization of services for such kinds of networks. This chapter has the goal of describing the relationships between multi-agent systems and social networks and how multi-agent systems technologies and techniques have been used and can be used in support of social networks.
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Agents and multi-agent systems are one of the most interesting areas in software research and they have been importantly contributing to the development of the theory and the practice of complex distributed systems (Jennings et al., 1995; Muller, 1998; Bordini et al., 2005).

Although there is no single definition of an agent – see, for example, (Genesereth & Ketchpel, 1994; Wooldridge & Jennings, 1995; Russel & Norvig, 2003) – all definitions agree that an agent is essentially a special software component that: i) has autonomy; ii) provides an interoperable interface to an arbitrary system and/or iii) behaves like a human agent, working for some clients in pursuit of its own agenda. In particular, an agent i) is autonomous, because it operates without the direct intervention of humans or others and has control over its actions and internal state; ii) is reactive, because it perceives its environment, and responds in a timely fashion to changes that occur in the environment; iii) is pro-active, because it does not simply act in response to its environment and it is able to exhibit goal-directed behaviour by taking the initiative. Moreover, if necessary, an agent can be i) mobile, showing the ability to travel between different nodes in a computer network; ii) truthful, providing the certainty that it will not deliberately communicate false information; iii) benevolent, always trying to perform what is required; iv) rational, always acting in order to achieve its goals, and never to prevent its goals being achieved, and v) it can learn, adapting itself to fit its environment and to the desires of its users.

Even if a complex system can be based on a solitary agent working within its environment–that may or may not comprise users – usually agent-based systems are realized in terms of multiple, interacting agents, i.e., agent-based systems are normally multi-agent systems. Multi-agent systems are generally considered an appropriate means for modelling complex, distributed systems, even if such a multiplicity naturally introduces the possibility of having different agents with potentially conflicting goals. Agents may decide to cooperate for mutual benefit, or they may compete to serve their own interests. Agents take advantage of their social ability to exhibit flexible coordination behaviours that make them able to both cooperate in the achievement of shared goals or to compete on the acquisition of resources and tasks. Agents have the ability of coordinating their behaviours into coherent global actions.

Key Terms in this Chapter

Social Network: social structure made of agents (individuals) which are connected by one or more different relationships

Utility: measure of the agent satisfaction mapping possible outcomes on elements of a totally ordered set (e.g., the set of real numbers with the < relation).

Expert Finding: the problem of distributed searching someone with a given set of skills and a given level of trust using a social network.

Coordination: a process in which a group of agents engages in order to ensure that each of them acts in a coherent manner.

Agent-Based Model: a class of computational models for simulating interacting agents.

Matchmaking System: a system to help people with similar interests get in touch.

Software Agent: a computer program that is situated in some environment and capable of autonomous action in order to meet its design objectives.

Multi-Agent System: a loosely coupled network of software agents that interact to solve problems that are beyond the individual capacities or knowledge of each software agent.

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