Editing Symbolic artificial intelligence (section)

====Approaches inspired by human or animal cognition or behavior====

Cybernetic approaches attempted to replicate the feedback loops between animals and their environments. A robotic turtle, with sensors, motors for driving and steering, and seven vacuum tubes for control, based on a preprogrammed neural net, was built as early as 1948. This work can be seen as an early precursor to later work in neural networks, reinforcement learning, and situated robotics.{{sfn|Kautz|2022|p=106}}

An important early symbolic AI program was the [[Logic theorist]], written by [[Allen Newell]], [[Herbert A. Simon|Herbert Simon]] and [[Cliff Shaw]] in 1955–56, as it was able to prove 38 elementary theorems from Whitehead and Russell's [[Principia Mathematica]]. Newell, Simon, and Shaw later generalized this work to create a domain-independent problem solver, [[General Problem Solver|GPS]] (General Problem Solver). GPS solved problems represented with formal operators via state-space search using [[means-ends analysis]].{{sfn|Newell|Simon|1972}}

During the 1960s, symbolic approaches achieved great success at simulating intelligent behavior in structured environments such as game-playing, symbolic mathematics, and theorem-proving. AI research was concentrated in four institutions in the 1960s: [[Carnegie Mellon University]], [[Stanford]], [[MIT]] and (later) [[University of Edinburgh]]. Each one developed its own style of research. Earlier approaches based on [[cybernetics]] or [[artificial neural network]]s were abandoned or pushed into the background.

[[Herbert A. Simon|Herbert Simon]] and [[Allen Newell]] studied human problem-solving skills and attempted to formalize them, and their work laid the foundations of the field of artificial intelligence, as well as [[cognitive science]], [[operations research]] and [[management science]]. Their research team used the results of [[psychology|psychological]] experiments to develop programs that simulated the techniques that people used to solve problems.{{sfn||McCorduck|2004|pp=139–179, 245–250, 322–323 (EPAM)}}{{sfn|Crevier|1993|pp=145–149}} This tradition, centered at Carnegie Mellon University would eventually culminate in the development of the [[Soar (cognitive architecture)|Soar]] architecture in the middle 1980s.{{sfn|McCorduck|2004|pp=450–451}}{{sfn|Crevier|1993|pp=258–263}}