Computational Intelligence

• Solving "hard" problems as intelligence
  • "the ability to solve problems is generally taken as a prime indicator that a system has intelligence" [NS p.X].
  • Many things can be viewed as problems, from mathematical problems to spiritual satisfaction.
  • Solving problems - Initial state, state generator, solution detector
  • Hard problems
    • Finding the Jamba Juice shop (see the Philosophical Answer)
    • O(E) and O(N^k) problems
  • Solving easy O(N^k) problems is easy.
  • Solving hard O(E) problems requires intelligence.
    • Random leaps of faith = O(E)
    • Exhaustive search = O(E)
    • With intelligence = O(N^k)
  • Intelligence is the ability to solve O(E) problems with O(N^k) resources,
    through the use of guided search (making hard problems look easy)
  • Representing the problem requires computer science, but no intelligence per se.
  • Solving the problem by guiding the search is the intelligence
    • Knowledge in terms of the symbols (syntactic)
    • Knowledge as a model of the environment (semantic)

• The Physical Symbol System Hypothesis - [CACM 19(3), pp.113-126]
  • Structure and composition
    • Symbols
    • Symbol structures
    • Wider world of objects (physical and conceptual), including processes that manipulate symbol structures
  • Symbol structures designate processes and objects.
    • The system can affect or react to the designated process or object.
    • Processes and objects are different, but are designated by the same things (symbol structures).
    • The thing that a symbol structure designates is determined by a separate mechanism. For symbol structures, the mechanism considers the arrangement of its constituent symbol structures.
    • Designation provides the semantics of the symbol structures.
  • Interpretation
    • A symbol structure designates a process by being the code that represents the process.
    • A symbol structure that designates a process can be executed.
  • Completeness and closure
    • A symbol may designate any object. Symbol structures designate objects according to their arrangement.
    • Symbol structures are Turing complete
    • There are processes for creating and manipulating symbol structures arbitarily.
    • Symbols and symbol structures are stable.
    • The system can hold infinite symbols and symbol structures (in principle).
  • The hypothesis: A physical symbol system has the necessary and sufficient means for general intelligent action.
    • Any system that is intelligent turns out to be a physical symbol system.
    • A physical symbol system of sufficient size can be organized to be intelligent.

Interesting Questions

1. What are the three components of a classic definition of a problem?
2. Describe the operation of the Turing test as a criteria for success in artificial intelligence.
3. Draw a labelled diagram showing the components of an intelligent agent.
4. What facet of Philosophy suggests that the mind operates according to physical laws? What implications does this have for AI?
5. Name three important contributions to AI from Mathematics.
6. Describe how the rapid improvements in computer hardware have advanced the capabilities of AI systems.
7. Name and briefly (maximum 20 words each) describe N AI application areas.
8. The Physical Symbol System hypothesis states that "A Physical Symbol System has the necessary and sufficient means for general intelligent action." What is the structure of a Physical Symbol System?
9. In the context of physical symbol systems, what are meant by "designation" and "interpretation"?
10. Describe the five requirements of completeness and closure for a physical symbol system.