Newell, Allen, and Herbert A. Simon

Objective: The authors aimed to demonstrate that human cognitive processes, particularly problem-solving, can be simulated using computer programs, thereby providing insights into human thinking.

Information Processing System (IPS): They proposed that both humans and computers can be viewed as information processing systems that manipulate symbols to solve problems.

Problem Space Concept: Introduced the idea of a "problem space," representing all possible states and actions in problem-solving, which both humans and machines navigate to reach solutions.

General Problem Solver (GPS): Developed the GPS program, an early AI system designed to mimic human problem-solving by employing heuristics to reduce the difference between the current state and the goal state.

Means-Ends Analysis: The GPS utilized means-ends analysis, a heuristic method that involves identifying differences between the current situation and the desired goal and then applying operators to reduce these differences.

Simulation of Cognitive Processes: By programming the GPS to solve problems, they aimed to simulate human cognitive processes, providing a framework to test psychological theories of thinking.

Empirical Validation: The authors compared the problem-solving behavior of the GPS with human subjects to validate the accuracy of their simulations, finding significant parallels.

Implications for Psychology: Their work suggested that complex human thought processes could be understood and analyzed through computational models, bridging psychology and computer science.

Limitations Acknowledged: They recognized that while the GPS could handle well-defined problems, it struggled with ill-defined problems requiring extensive real-world knowledge.

Foundation for AI Research: This study laid the groundwork for future developments in artificial intelligence and cognitive psychology by illustrating the potential of computer simulations to model human thought.