Building a multiagent system

A multiagent system is dependent on interactions between intelligent agents.

There are, therefore, some key design decisions to be made, e.g., when, how, and with whom should agents interact? In cooperative models, several agents try to combine their efforts to accomplish as a group what the individuals cannot. In competitive models, each agent tries to get what only some of them can have. In either type of model, agents are generally assumed to be honest.

In order to achieve coherency, multiagent systems can be designed bottom-up or top-down. In a bottom-up approach, agents are endowed with sufficient capabilities, including communication protocols, to enable them to interact effectively. The overall system performance then emerges from these interactions. In a top-down approach, conventions — sometimes called societal norms — are applied at the group level in order to define how agents should interact. An example might be the principle of democracy, achieved by giving agents the right to vote. If we view an agent as having a knowledge level abstracted above its inner mechanisms, then these conventions can be seen as residing at a still higher level of abstraction, namely the social level (Figure 5.4).

Multiagent systems are often designed as computer models of human functional roles. For example, we may have a hierarchical control structure in which one agent is the superior of other subordinate agents. Peer group relations, such as may exist in a team-based organization, are also possible.

This section will address three models for managing agent interaction, known as contract nets [13], cooperative problem solving (CPS) [14, 15] and shifting matrix management (SMM) [16]. After considering each of these models in turn, the semantics of communication between agents will be addressed.

Bottom up Top down

Social level

Knowledge level

Mechanism level

Figure 5.4 Agent levels of abstraction

Contract nets

Imagine that you have decided to build your own house. You are unlikely to undertake all the work yourself. You will probably employ specialists to draw up the architectural plans, obtain statutory planning permission, lay the foundations, build the walls, install the floors, build the roof, and connect the various utilities. Each of these specialists may in turn use a subcontractor for some aspect of the work. This arrangement is akin to the contract net framework [13] for agent cooperation (Figure 5.5). Here, a manager agent generates tasks and is responsible for monitoring their execution. The manager enters into explicit agreements with contractor agents willing to execute the tasks. Individual agents are not designated a priori as manager or contractor.

These are only roles, and any agent can take on either role dynamically during problem solving.

To establish a contract, the manager agent advertises the existence of the tasks to other agents. Agents that are potential contractors evaluate the task announcements and submit bids for those to which they are suited. The manager evaluates the bids and awards contracts for execution of the task to the agents it determines to be the most appropriate. The manager and contractor are thus linked by a contract and communicate privately while the

Manager

Bidder

Bidder

Manager

Contractor

(a) (b)

(c) (d)

Manager

Figure 5.5 Contract nets [13]:

(a) Manager advertises a task; (b) potential contractors bid for the task;

(c) manager awards the contract; (d) manager and contractor communicate privately

contract is being executed. The managers supply mostly task information and the contractor reports progress and the eventual result of the task. The negotiation process may recur if a contractor subdivides its task and awards contracts to other agents, for which it is the manager.

CPS framework

The cooperative problem-solving (CPS) framework is a top-down model for agent cooperation. As in the BDI model, an agent’s intentions play a key role.

They determine the agent’s personal behavior at any instant, while joint intentions control its social behavior [17]. An agent’s intentions are shaped by its commitment, and its joint intentions by its social convention. The framework comprises the following four stages, also shown in Figure 5.6:

Stage 1: recognition. Some agents recognize the potential for cooperation with an agent that is seeking assistance, possibly because it has a goal it cannot achieve in isolation.

Stage 2: team formation. An agent that recognized the potential for cooperative action at Stage 1 solicits further assistance. If successful, this stage ends with a group having a joint commitment to collective action.

Stage 3: plan formation. The agents attempt to negotiate a joint plan that they believe will achieve the desired goal.

Stage 4: team action. The newly agreed plan of joint action is executed. By adhering to an agreed social convention, the agents maintain a close-knit relationship throughout.

Stage 1: recognition

Stage 2: team formation

Stage 3: plan formation

Stage 4: team action team disbands

Figure 5.6 CPS framework

Shifting Matrix Management (SMM)

SMM [16] is a model of agent coordination that has been inspired by Mintzberg’s Shifting Matrix Management model of organizational structures [18], as illustrated in Figure 5.7. Unlike the traditional management hierarchy, matrix management allows multiple lines of authority, reflecting the multiple functions expected of a flexible workforce. Shifting matrix management takes this idea a stage further by regarding the lines of authority as temporary, typically changing as different projects start and finish. For example, in Figure 5.7, individual #1 is the coordinator for project A and the designer for project B. In order to apply these ideas to agent cooperation, a six-stage framework has been devised (Figure 5.8) and outlined below. The agents are distinguished by their different motives, functionality, and knowledge. These differences define the agents’ variety of mental states with respect to goals, beliefs, and intentions.

Stage 1: goal selection. Agents select the tasks they want to perform, based on their initial mental states.

project A project B project C project D

coordinator

designer

tester

programmer

author

#1 #2 #3 #1

#2 #1

#2

#2 #3

#4 #5

#5

#5 #3

#1 #2

#4

Figure 5.7 Shifting Matrix Management (SMM): the nodes represent people [18]

Stage 2: individual planning. Agents select a way to achieve their goals. In particular, an agent that recognizes its intended goal is common to other agents would have to decide whether to pursue the goal in isolation or in collaboration with other agents.

Stage 3: team formation. Agents that are seeking cooperation attempt to organize themselves into a team. The establishment of a team requires an agreed code of conduct, a basis for sharing resources, and a common measure of performance.

Stage 4: team planning. The workload is distributed among team members.

Stage 5: team action. The team plan is executed by the members under the team’s code of conduct.

Stage 6: shifting. The last stage of the cooperation process, which marks the disbanding of the team, involves shifting agents’ goals, positions, and roles.

Each agent updates its probability of team-working with other agents, depending on whether or not the completed team-working experience with that agent was successful. This updated knowledge is important, as iteration through the six stages takes place until all the tasks are accomplished.

Stage 1: goal selection

Stage 2: individual planning

Stage 3: team formation

Stage 4: team planning

Stage 5: team action

Stage 6: shifting

Figure 5.8 SMM multiagent framework