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Subsumption architecture

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Subsumption architecture is an AI concept originating from behavior based robotics. This term was invented by Rodney Brooks and colleagues in the mid to late 1980s.

A subsumption architecture is a way of decomposing one complex behaviour into many "simple" layers of increasing more abstract behaviours. Each layer can use (subsume) the underlaying layer, e.g. the decision to move forward by the eat-food layer takes in account the decision of the lowest obstacle-avoidance layer.

For example, a robot's lowest layer could be "avoid an object", on top of it would be the layer "wander around", which in turn lies under "explore the world". The top layer in such a case could be "create a map", which is the ultimate goal. Each of these horizontal layers accesses all of the sensor data and generates actions for the actuators — the main caveat is that separate tasks can inhibit inputs or overrule outputs. This way, the lowest layers can work like fast-adapting mechanisms (reflexes), while the higher layers control the main direction to be taken in order to achieve the overall goal. Feedback is given mainly through the environment.

Two main disadvantage of this model are the inability to modularise the system and the rather low flexibility at runtime.

This AI model was invented by Alexandre Parodi, and was first used in a real robot as part of the FMC/CEL (now United Defense) AVTB/AGVT program in 1984. All this research is described in a series of academic papers, many written with students and collaborators such as Pattie Maes and Anita M. Flynn. Key amongst these are, arguably:

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