General Problem Solver

Definition

The General Problem Solver (GPS) is an early artificial intelligence program developed by Allen Newell and Herbert A. Simon in the 1950s, designed to simulate human problem-solving processes. It aimed to represent a broad range of problem-solving strategies and could be applied to various domains, making it foundational for the development of AI systems. The GPS was significant for its ability to break down complex problems into manageable steps, employing heuristics and algorithms to find solutions.

5 Must Know Facts For Your Next Test

1. The General Problem Solver was one of the first programs to attempt to mimic human cognitive processes in solving problems across different domains.
2. GPS utilized a means-ends analysis approach, which involves breaking a problem down into smaller subgoals to achieve the final solution.
3. Despite its innovative design, GPS had limitations and struggled with more complex problems that required deeper understanding or reasoning.
4. The development of GPS highlighted the importance of heuristics in problem-solving, influencing later AI research and applications.
5. Newell and Simon's work on GPS contributed significantly to cognitive science by demonstrating how computational models could replicate human thought processes.

Review Questions

• How did the General Problem Solver use means-ends analysis in its approach to problem-solving?
  • The General Problem Solver employed means-ends analysis by breaking down complex problems into smaller, more manageable subgoals. This method allowed the program to focus on achieving each subgoal step by step until it reached the overall solution. By doing so, GPS effectively mirrored a common strategy used in human problem-solving, making it an early example of how AI could replicate cognitive processes.
• Discuss the limitations of the General Problem Solver and how these limitations influenced future AI developments.
  • While the General Problem Solver was groundbreaking, it faced significant limitations, particularly with complex problems that required deeper reasoning or contextual understanding. This highlighted the need for more sophisticated approaches in AI research. As a result, future developments focused on enhancing algorithms and incorporating additional cognitive principles, leading to more robust and flexible AI systems capable of handling a wider range of tasks.
• Evaluate the impact of Newell and Simon's work on the General Problem Solver on the fields of artificial intelligence and cognitive science.
  • Newell and Simon's development of the General Problem Solver marked a pivotal moment in both artificial intelligence and cognitive science. Their approach laid the groundwork for understanding how computational models can simulate human cognition, influencing later research in these fields. The principles established by GPS regarding problem-solving strategies and heuristics continue to inform AI design and cognitive theories, demonstrating its lasting legacy in shaping our understanding of intelligence.

Related terms

Heuristic: A simple, efficient rule or method used to make decisions or solve problems quickly, often based on experience rather than a guaranteed optimal solution.

Algorithm: A step-by-step procedure or formula for solving a problem or performing a task, which can be implemented in computer programming.

Cognitive Architecture: A theoretical framework that aims to describe the structure and functioning of the human mind, often used in AI research to create models of human cognition.