Symbolism

Symbolism or Symbolist, the practice of representing things by symbols, or of investing things with a symbolic meaning or character, is a 19th-century artistic movement rejecting Realism. A symbol is an object, action, or idea that represents something other than itself, often of a more abstract nature.

To provide some intuition, a first definition of a symbolic architecture is an architectures that utilizes symbol manipulations in a fixed manner to represent its processing. Subsymbolic architectures do not use symbols to represent their processing. A common alternative to symbolism is to use analog representations and transformations.

Now the term symbolic architectures will be defined in more detail. A natural question to ask 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 there to be: (a) sufficient memory, (b) composibility (that the operators may make any symbol structure), and (c) 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. That it is fixed implies that the behavior of structures on top of it (i.e. "programs") mainly depends 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;

- 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 (the flip-side of 1)

- They maybe made computationally complete (e.g. Turing Machines)

  Examples of symbolic architectures are;

  Atlantis by E. Gat.

  Dynamic Control Architecture by B. Hayes-Roth.

  ERE by Drummond et al.

  Homer by Vere & Bickmore.

  Icarus by Langley.

  MAX by D. Kuokka.

  Prodigy by Carbonell et al.

  RALPH by Ogasawara and Russell.

  SOAR by A. Newell et al.

  Teton by VanLehn & Ball.

  Theo by T. Mitchell et al.