Affiliations: Defence, Science and Technology Group Edinburgh, PO Box 1500, Edinburgh SA 5111, Australia. E-mail: [email protected]
Abstract: The design and implementation of hybrid intelligent systems is gaining pace.
Intelligent Multi-Agent System (I-MASs) are being designed and developed for dynamic and contested environments, allowing systems to exercise and act upon unfamiliar, and at times progressive events. Hybrid and intelligent systems require an I-MAS to support multiple participants, each with its own view of the environment and that has the ability to perceive, decide and act on events. To ensure cohesion and goal-driven behaviours are conducted, Coordination and Cooperation (Coo^2) techniques need to be revisited. Current Coo^2 techniques fail to recognise the importance of mental modelling and situation assessment of agents. Moreover, cognitive and reasoning architectures, like Observe-Orient-Decide-Act (OODA) and Belief, Desire and Intention (BDI) do not consider how organisational principles, like Coo^2, can assist in how an agent behaves when dealing with an event. The Agent Coordination and Cooperation Cognitive Model (AC^3M) is a new generation of agent-based models that will exploit an agent's cognitive and mental architectures to strengthen Coo^2. This is achieved by establishing processes that exhibit how an agent's stimulation, orientation and belief-set is related to its ability to coordinate and be coordinated. AC^3M also illustrates how decision-making processes and an agent's ability to act is connected to its desires and intentions. In addition, the relationship between decision and action and desires and intentions provides the foundations for cooperation between agents. Integrating elements within BDI and Stimulate-Orient-Decide-Act (SODA)
produces superior and complex Coo^2 techniques. Consequently, by associating beliefs and orientation to coordination, as well as desire, intentions to cooperation will strengthen and improve situation awareness and decision-making, which is critical in dynamic environments.
