Symbols and Representation
Symbols and Representation
A natural question to ask about symbols and representation is what is a symbol?
Allen Newell considered this question in
Unified Theories of Cognition.
He differentiated between symbols (the phenomena in the abstract) and
tokens (their physical instantiations).
Tokens "stood for" some larger concept.
They could be manipulated locally until the information in the larger concept
was needed, when local processing would have to stop and access
the distal site where the information was stored.
The distal information may itself be symbolically encoded, potentially leading
to a graph of distal accesses for information.
Newell defined symbol systems according to their characteristics.
Firstly, they may form a universal computational system.
They have
- memory to contain the distal symbol information,
- symbols to provide a pattern to match or index distal information,
- operations to manipulate symbols,
- interpretation to allow symbols to specify operations, and,
- capacities for:
- sufficient memory,
- composability (that the operators may make any symbol structure),
- interpretability (that symbol structures be able to encode any
meaningful arrangement of operations).
Finally, Newell defined symbolic architectures as the fixed structure
that realizes a symbol system.
The fixity implies that the behavior of structures on top of it
(i.e. "programs") mainly depend upon the details of the symbols,
operations and interpretations at the symbol system level, not upon how
the symbol system (and its components) are implemented.
How well this ideal hold is a measure of the strength of that
level.
The advantages of symbolic architectures are:
- much of human knowledge is symbolic, so encoding it in a computer is more
straight-forward;
- how the architecture reasons may be analogous to how humans do, making it
easier for humans to understand;
- they may be made computationally complete (e.g. Turing Machines).
These advantages have been considered as
one of the fundamental tenets of
artificial intelligence known as the
physical symbol system hypothesis. The hypothesis proposes that a physical
symbol system has the necessary and sufficient means for general
intelligence.
Symbols represent knowledge -- including
models of the world. Thus, at levels above the symbol
(or architecture) level, knowledge may mediate behavior. This level is
known as the knowledge level.
Newell characterizes the symbol level in
humans as the
cognitive band.
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