The General Problem Solver (GPS) is an early AI program developed in 1957 by Allen Newell and Herbert A. Simon at the RAND Corporation.
🎯 Goal: To create a program that could solve any well-defined problem, using human-like reasoning.
GPS has two main components:
| Component | Description |
|---|---|
| Goal Structure | Keeps track of the current goal and subgoals |
| Means-Ends Analysis Engine | Compares current and goal states, selects actions to reduce differences |
🧠 This mimics how humans solve problems: break big goals into smaller steps.
Problem: Prove a theorem in logic Operators: Rules of inference (e.g., Modus Ponens) Goal: Derive a conclusion from premises GPS uses its logic rules to reach the target conclusion step-by-step.
✅ Introduced means-ends analysis, a major idea in AI ✅ Showed that general-purpose problem solving is possible ✅ Was an early model of human cognitive processes
| Limitation | Explanation |
|---|---|
| Not scalable | Worked only on simple or toy problems |
| Needs formal problem definition | Struggles in complex or poorly-defined domains |
| No learning ability | Did not adapt or improve over time |
| Domain knowledge was limited | Couldn’t handle rich real-world tasks |
| Feature | Details |
|---|---|
| Name | General Problem Solver (GPS) |
| Developers | Allen Newell & Herbert A. Simon |
| Year | 1957 |
| Method | Means-Ends Analysis |
| Purpose | Solve general problems like a human |
| Impact | Influential in early AI and cognitive science |
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