These are some extra notes about BOD which might be of interest to
academics... they used to be on the main BOD web
Decomposing intelligence into behavior modules & reactive plans not only simplifies the design of an agent, it also supports learning by that agent. Learning and the details of perception and action are contained in relatively simple, single-purpose behavior modules. Where the actions of different behavior modules might interfere with each other, coordination is provided by the attention system. The attention system uses the reactive plans to determine priorities given the agent's current focus (its recent decisions) and the current environmental context. The reactive planning system used by BOD is called POSH action selection.
The architecture underlying BOD differs from most "hybrid" or
three-layer architectures by emphasizing the power and importance of
the behavior modules. These are semi-autonomous agencies, maintaining
their own state as necessary for perception, learning or control.
They may control actions independently of the agent-level action
selection, so long as their activity doesn't interfere with other
behaviors. The leaf nodes of the reactive plans are a method-based
interface to the behaviors. One behavior will generally support a
large number of plan primitives.
BOD differs from most strictly behavior-based systems in that it
provides a mechanism (POSH) and methodology to make behavior
arbitration / coordination easy for ordinary programmers. (Most
programmers have difficulty reasoning about parallel systems.) It
differs from some other agent methodologies by actively supporting the
modification of early specifications. (I am not a creationist.)