Multiagent systems and Societies of Agents
Analyzing and considering only individual agent architecture is neither convenient nor realistic as most environments contain multiple agents interacting together in various ways. An important aspect of these multiagent systems or societies of agents consists of the infrastructure facilitating the interaction between agents during their course of action. These interactions should not compromise autonomy of agent whether they are cooperative, competitive or simply self-interested.
During message exchanging, some form of protocol or mechanisms dictating the communication are necessary to ensure that agents “understand” each other. These protocols are defined at various communication levels. We have, from lowest to highest respectively, level specifying interconnection, level responsible of format and syntax and level for meaning or semantic. At a more abstract level, another protocol is also necessary to organize interaction between agents as to mimic “real conversation” taking place not just single message exchanged.
Communication Level Protocol
To simplify software agent design, “speech act theory” serves as a model for handling the various aspect of communication. Speech act views human language as actions (e.g. request, suggestion, commitment, replies, etc). These actions have three dimensions; locution (the words), illocution (the intended meaning) and the perlocution (the actions resulted of the locution).
One good example of a protocol for exchanging information and knowledge that rely on “speech act theory” performative model is called KQML (or Knowledge Query and Manipulation Language). This protocol is specifically useful for decoupling both the message and the communication semantic. This is achieved by separating the message into multiple fields; language (e.g. Knowledge Interchange Format -KIF or Lisp, Prolog, etc), content (i.e. representing the message itself and expressed using the language specified) and ontology (representing the objects and their inter-relationship in a domain of interest) are all part of separate fields.
Interaction Level Protocol
As for the higher level of communication, concepts such as coordination, cooperation, contract net, blackboard system, negotiation and market mechanisms have all been devised in order to specify agent interaction protocol.
Coordination protocol ensures that global goals are achieved while respecting global constraint and reducing redundant problem solving. Coordinated systems have often been designed in DAI field (distributed artificial intelligence) through techniques that distribute both control and data. However, this leads to some difficulty such as agents having only partial and imprecise information knowledge on the global goals and also having less coherent global behaviour. Coordination uses two keys structures to formalize itself in distributed agent system. The first one called commitment is used by the agent as a pledge to undertake a specified course of action, while the second one called convention is a means of managing commitments in changing circumstances. Commitment ties agent into future activities and convention dictates the rules and constrains under which these commitments are re-evaluated in case of changes and new reality.
Coordination is not the only abstract level protocol existing, the following gives a brief definition of alternative mechanisms existing to support agent interaction:
Task decomposition and distribution. Often utilized in a more cooperative type environment in which the system designer takes care of the task decomposition of agents. This can be done by spatial decomposition where agents are responsible of task based on the information source and decision point location, or by functional decomposition where agents are defined and allocated by expertise.
Contract Net. This mechanism is modelled following the goods/services exchange economic rule. The roles of agent are not specified before hand but rather through a bidding system in which managers (agent announcing task for bidding) award contractors (agent winning a contract after submitting a bid) specific problem resolution task.
BlackBoard System. Central interaction point shared and used by all agents to reach common solution.
Negotiation. Utilized in situation involving agents having conflicting goal. This needs some form of concession and alternatives search from the agents to reach and move toward agreements.
Market mechanism. Often a direct interaction between agents is just impossible due to the significant number of agents involved. In this scheme, a voting system can be put in place allowing agents to vote between a set of alternatives solution proposed by a smaller group of agent.
Taken from
“Multiagent Systems, a Modern Approach to Distributed Modern Approach to Artifical Intelligence” Chapter 2 Mutliagents Systems and Societies of Agents, Huhns and Stephens (1999)
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