Programming Considerations

Programming Considerations

It is interesting to note that the use of predicate logic and recursion by Strips
favors languages like Lisp and PROLOG. These languages were developed
by AI researchers specifically for expressing logical operations. These languages
do not necessarily have good real-time control properties like C or
C++. However, during the 1960’s the dominant scientific and engineering
language was FORTRAN IV which did not support recursion. Therefore, researchers
in AI robotics often chose the lesser of two evils and programmed
in Lisp. The use of special AI languages for robotics may have aided the split
between the engineering and AI approaches to robotics, as well as slowed
down the infusion of ideas from the the two communities. It certainly discouraged
non-AI researchers from becoming involved in AI robotics.
The Hierarchical Paradigm tends to encourage monolithic programming,
rather than object-oriented styles. Although the NHC decomposes the planning
portion of intelligence, the decomposition is strictly functional. In particular,
NHC and RCS don’t provide much guidance on how to build modular,
reusable components.

Summary

The Hierarchical Paradigm uses a SENSE then PLAN then ACT (S,P,A). It
organizes sensing into a global data structure usually called a world model
that may have an associated knowledge base to contain a priori maps or
knowledge relevant to a task. Global data structures often flag that an ar-

chitecture will suffer from the frame problem. The Hierarchical Paradigm
was introduced in the first mobile robot, Shakey. Strips is an important planning
technique that came out of the Shakey project at SRI, which focused
on the PLAN primitive in robotics. Concepts and terms which emerged that
continue to play an important role in defining robotics are: preconditions,
the closed and open world assumptions, and the frame problem. Hierarchical
systems have largely fallen out of favor except for the NIST Realtime
Control Architecture. The decline in popularity is due in part to its focus on
strong niche targetability at the expense of true modularity and portability.
However, as will be seen in the following chapters, insights from biology and
cognitive science have led to paradigms with more intuitive appeal. One often
overlooked property ofmost hierarchical architectures is that they tend to
support the evolution of intelligence from semi-autonomous control to fully
autonomous control.