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achieve the global objective Jennings et al., 1998; Ferber, 1999. Knowledge and
control are distributed, in the sense that each agent embodies its own knowledge and control.
2.5.3 MAS interactions
MAS achieve its objectives through interactions between agents. The interactions can be categorised as cooperation, coordination, and negotiation Jennings
et al., 2001. According to Doran
et al. 1997, cooperation occurs when the actions of each agent satisfy either or both of the following conditions: agents have a possible goal in
common, which no agent could achieve in isolation; agents perform actions, which enable or achieve not only their own goals, but also the goals of agents other than
themselves. Jennings 1996 defines coordination as the process by which an agent reasons about its
local actions and the anticipated actions of others to try and ensure the community acts in a coherent manner. According to Nwana et al. 1996, coordination is a process in
which agents engage in order to insure their community acts in a coherent manner. Coherent means that the agents’ actions work well, and that they do not conflict with
one another. The main approaches that have been developed for coordinating activities are centralised planning, multi-agent planning, game theory, and negotiation Nwana et
al., 1996; Jennings, 1996; Ferber, 1999; Wooldridge, 2002. Negotiation is a widely used technique for conflict resolution in MAS. It is the most
fundamental and powerful mechanism for managing inter-agent dependencies. Negotiation is the communication process of a group of agents in order to reach a
mutual accepted agreement on some matter Bussman and Muller, 1992. For Wooldridge 2002, negotiation proceeds in a series of rounds with every agent making
proposals, trading options and offering concessions at every round. The proposals that agents make are defined by their strategy, must be drawn from the negotiation set, and
must be legal, as defined by the protocol. If agreement is reached, as defined by the agreement rule, then negotiation terminates with the agreement deal. Jennings et al.
2001 defined a generic framework of negotiation. In this framework, negotiation can be viewed as a distributed search through a space of potential agreements. For a given
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negotiation, the participants are the active components that determine the direction of the search. The minimum requirement of a negotiating agent is the ability to make and
respond to proposals. To improve the efficiency of the negotiation process, the recipient needs to be able to provide more useful feedback on the proposals it receives. Various
negotiation methods have been defined in literature, and most of them are inspired by human negotiations that are market-based, plan-based, game theory-based, and artificial
intelligence based. Kraus, 1997; Faratin et al., 1998; Jennings et al., 2001. Market-based negotiation is the simplest and the most renowned negotiation protocol,
and the most widely used in agent-based systems is the contract net protocol involving offers, bids, and contracts Nwana et al., 1996; Beer et al., 1999; Shen and Norrie,
1999; Jennings et al., 2001; Shen et al., 2001. It is a high-level negotiation protocol
that provides many advantages and most important is its flexibility and dynamic nature, which suits industrial agent-based applications.
Plan-based negotiation is based on cooperation strategies for resolving conflicts among plans of a group of agents. Laasri and Lesser 1990 described a three-phase cycle
negotiation plan. This model of negotiation could be centralised or distributed. Game theory-based negotiation employs techniques based on game theory to structure
and organise negotiation between the agents Nwana et al., 1996; Jennings et al., 2001. The key concepts in the game theory approaches are utility functions, a space of deals,
strategies, and negotiation protocols. Artificial Intelligence based negotiation considers negotiation as an iterative activity
and Sycara 1991 exploited case-based reasoning in this iterative process. Sycara 1991 argued that human negotiators draw from past negotiation experiences to guide
present and future decisions.
2.5.4 MAS Communication
