Most work done in distributed artificial intelligence (DAI) had targeted sensory networks, including air traffic control, urban traffic control, and robotic systems. The main reason is that these applications necessitate distributed interpretation and distributed planning by means of intelligent sensors. Planning includes not only the activities to be undertaken, but also the use of material and cognitive resources to accomplish interpretation tasks and planning tasks. These application areas are also characterized by a natural distribution of sensors and receivers in space. In other words, the sensory data-interpretation tasks and action planning are inter-dependent in time and space. For example, in air traffic control, a plan for guiding an aircraft must be coordinated with the plans of other nearby aircraft to avoid collisions.
Industrial applications of distributed AI
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