Case Study: General Problem Solver

📘 Case Study: General Problem Solver (GPS)

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1. What is the General Problem Solver (GPS)?

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.

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2. Objectives of GPS

• Model human problem-solving behavior.
• Work on a wide range of problems (not just one domain).
• Separate general problem-solving techniques from domain knowledge.

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3. Architecture of GPS

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

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4. How GPS Works (Means-Ends Analysis)

1. Compare the current state with the goal state.
2. Identify differences between them.
3. Select an operator (action) that reduces one of the differences.
4. If an operator has a precondition, set that as a new subgoal.
5. Continue until the goal is achieved.

🧠 This mimics how humans solve problems: break big goals into smaller steps.

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5. Example Problem Solved by GPS

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.

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6. Strengths of GPS

✅ 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

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7. Limitations of GPS

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

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✅ Summary

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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