Symbolic AI, also called Good Old-Fashioned AI (GOFAI), emerged in the 1950s as the dominant approach to artificial intelligence research. This paradigm assumed that intelligence could be reduced to the manipulation of symbols and logical rules, mirroring human reasoning through explicit representation of knowledge.

Foundational Developments

The field crystallized at the Dartmouth Summer Research Project on Artificial Intelligence held in Hanover, New Hampshire in 1956, where pioneers including John McCarthy, Marvin Minsky, Nathaniel Rochester, and Claude Shannon gathered to explore machine reasoning. McCarthy coined the term "artificial intelligence" at this conference.

Key Milestones and Works

• Logic Theorist (1956) - considered the first AI program, developed at Carnegie Institute of Technology in Pittsburgh
• General Problem Solver (1957) - created by Minsky and McCarthy to simulate human problem-solving protocols
• ELIZA (1966) - Joseph Weizenbaum's chatbot demonstrated at MIT, which simulated a psychotherapist with 36 built-in rules

Peak and Decline

Symbolic AI dominated from the 1960s through 1980s, generating optimistic predictions that machines would achieve human-level intelligence. However, limitations became apparent by the late 1980s. The approach struggled with tasks requiring pattern recognition and learning from experience, leading to the AI winter of the 1990s when funding declined significantly across universities and research institutions worldwide.

Reference:

Wikipedia reference

https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence