Distributed Artificial Intelligence involves solving complex problems requiring computation in spatial distribution of computing resources.
DAI systems consist of autonomous processing nodes, that are distributed, possibly at a large scale. DAI nodes can act independently and partial solutions are integrated by communication between nodes, often asynchronously. By virtue of their scale, DAI systems are robust and flexible and by necessity loosely coupled.
In DAI, systems (agents) coordinate their knowledge and activities and reason about the processes of coordination. Systems are physical or virtual entities that can act, perceive their environment and communicate with other systems. Systems are autonomous, have skills to achieve goals and are able to change the state of their environment by their actions. There are a number of different coordination techniques. Typically, work is divided among nodes and knowledge is shared, so that task decomposition and synthesis of the knowledge and solutions become the main concerns. Moreover, distributed AI is about:
- how to carry out communication and interaction and which communication language and protocols to be used
- how to ensure coherency
- how to synthesize results by formulation, description, decomposition and allocation