Report on a General-Problem Solving Program (1959)

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Created: May 12, 2016 / Updated: November 2, 2024 / Status: finished / 3 min read (~463 words)
Artificial General Intelligence

  • The major features of the program that are worthy of discussions are:
    • The recursive nature of its problem-solving activity
    • The separation of problem content from problem-solving technique as a way of increasing the generality of the program
    • The two general problem-solving techniques that now constitute its repertoire: means-ends analysis, and planning
    • The memory and program organization used to mechanize the program
  • The principal means of investigation is synthesis: programming large digital computers to exhibit intelligent behavior, studying the structure of these computer programs, and examining the problem-solving and other adaptive behaviors that the programs produce
  • A genuine problem-solving process involves the repeated use of available information to initiate exploration, which discloses, in turn, more information until a way to attain the solution is finally discovered

  • GPS operates on problems that can be formulated in terms of objects and operators
  • An operator is something that can be applied to certain objects to produce different objects
  • The objects can be characterized by the features they possess, and by the differences that can be observed between pairs of objects
  • Operators may be restricted to apply to only certain kinds of objects; and there may be operators that are applied to several objects as inputs, producing one or more objects as output
  • To operate generally within a task environment characterized by objects and operators, GPS needs several main components:
    • A vocabulary, for talking about the task environment
    • A vocabulary, dealing with the organization of the problem-solving processes
    • A set of programs defining the terms of the problem-solving vocabulary by terms in the vocabulary for describing the task environment
    • A set of programs applying the terms of the task-environment vocabulary to a particular environment: symbolic logic, trigonometry, algebra, integral calculus
  • To specify problems and subproblems, GPS has a discrete set of goal types
  • With each goal type is associated a set of methods related to achieving goals of that type
  • When an attempt is made to achieve a goal, it is first evaluated to see whether it is worthwhile achieving and whether achievement seems likely
  • All the heuristics apply the following general principle:
    • The principle of subgoal reduction: Make progress by substituting for the achievement of a goal the achievement of a set of easier goals

  • This planning method consists in
    • abstracting by omitting details of the original objects and operators
    • forming the corresponding problem in the abstract task environment
    • when the abstract problem has been solved, using its solution to provide a plan for solving the original problem
    • translating the plan back into the original task environment and executing it