Symbol Processing in Artificial Intelligence

Image Understanding
Obviously, there is a wide gap between the nature of images (essentially arrays of numbers) and descriptions. It is the bridging of this gap that has kept researchers very busy over the last two decades in the fields of Artificial Intelligence.
aaai.org/AITopics/ImageUnderstanding
Natural Language Processing    AI Programming Systems & Languages    Representation   

Symbolic Artificial Intelligence
Symbolic AI is a very attractive area of AI with its focus on the Mind's symbolic processing... Workers in AI in one way or another study intelligence as symbolic computation. In particular, they work with physical symbol systems.
cs.st-andrews.ac.uk/~mkw/IC_Group/symbolicai.html

The Pattern Recognition Basis of AI
Symbol processing techniques are not working out very well and these methods alone will never be able to give the depth and breadth of capabilities found in human beings.
dontveter.com/basisofai/basisofai.html
A comp.ai.philosophy FAQ   

Physical symbol system - wikipedia.org
The physical symbol system hypothesis (PSSH) is a position in the philosophy of artificial intelligence formulated by Allen Newell and Herbert Simon.
en.wikipedia.org/wiki/Physical_symbol_system
Symbol grounding    MIT Artificial Intelligence Laboratory    Philosophy of artificial intelligence   

Artificial Intelligence: Can a Machine Think?
Is it possible to build a machine that is intelligent? That can think?
mind.ilstu.edu/curriculum/modOverview.php?modGUI=228
Robots using Symbols   

The Meanings of "Meaning"
Herbert Simon has long been a leading advocate of a dominant role for symbol processing within artificial intelligence, going so far as to posit, in his and Alan Newell's "physical symbol system hypothesis," that being a physical symbol system is both a necessary and sufficient condition for being intelligent.
stanford.edu/group/SHR/4-1/text/korb.commentary.html

No Easy Way Out - Telekinetic Dualism
Explaining consciousness -- the how and why of human feeling -- is such a hard problem that it may never yield to cognitive science.
users.ecs.soton.ac.uk/harnad/Tp/thesciences.htm