CONCEPTS & TURNING POINTS / 2 MIN READ
Symbolic AI and the "Golden Age" (1956–1970s)
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The early decades of AI were dominated by symbolic, rule-based approaches to reasoning. This sub-article expands Section 3 of History.
Search and Problem Solving
- Logic Theorist and General Problem Solver demonstrated that machines could manipulate symbols to prove theorems and plan actions.
- Search algorithms (A*, heuristic search, constraint satisfaction) became core tools.
Game Playing
- Arthur Samuel’s checkers program (1959) used self-play and learning.
- Later, chess programs improved steadily toward Deep Blue (1997).
Languages and Tools
- Lisp (McCarthy, 1958) became the dominant AI language, with garbage-collected list processing.
- Prolog (1970s) enabled logic programming and declarative knowledge representation.
Neural Networks Enter and Retreat
- Perceptron (Rosenblatt, 1958) was a simple learning network.
- Minsky & Papert’s Perceptrons (1969) showed limits of single-layer perceptrons, dampening neural research for years.
Robotics and Planning
- Shakey the robot (Stanford, 1966–1972) autonomously planned, perceived, and navigated.
- STRIPS (1971) formalized planning in terms of preconditions and effects.
Why It Matters
Symbolic AI established reasoning, representation, search, and planning as core AI problems. Its strengths (explainability, logic) and weaknesses (brittleness, knowledge engineering) shaped later cycles.
Sources
- Newell, A. & Simon, H. (1972). Human Problem Solving.
- Minsky, M. & Papert, S. (1969). Perceptrons.
- Fikes, R. & Nilsson, N. (1971). STRIPS: A New Approach to the Application of Theorem Proving to Problem Solving.
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