good old-fashioned AI
In plain wordsA nickname for the classic style of AI, dominant from the 1950s to the 1980s, that tried to make computers intelligent by writing knowledge and rules down by hand.
Symbolic AIsymbolic AI, n.: An approach to AI that writes knowledge down as human-readable symbols and rules, such as 'every bird has wings', and reasons by manipulating them step by step instead of learning patterns from data. in its classical form: systems whose intelligence is meant to reside in explicit, hand-crafted representations — logical axioms, rules, framesframe, n.: In classic AI, a ready-made template for a familiar kind of thing or event, such as a kitchen or a job interview, with blanks to fill in and sensible default values. — manipulated by search and inference, as in GPSGeneral Problem Solver, prop. n.: A 1950s program meant to solve any well-defined puzzle by repeatedly comparing where it was with where it wanted to be and choosing steps that closed the gap., SHRDLUSHRDLU, prop. n.: A program from around 1970 that let people move toy blocks in a simulated world by typing ordinary English commands and questions, and that could explain what it had done and why. and expert systemsexpert system, n.: A program that stores a human specialist's know-how as many if–then rules and uses them to give advice or make decisions in a narrow field, such as diagnosing infections or configuring computers.. On John Haugeland's account, the approach rests on two bets: that intelligent behavior stems from reasoning about the world, and that reasoning is, at bottom, automatic processing of symbols held inside the system. Philosophers, historians and critics use the label to set this program apart from connectionismconnectionism, n.: The view that minds and intelligent machines are best built from huge networks of simple, neuron-like units whose connection strengths are learned, rather than from explicit rules and symbols., statistical machine learningmachine learning, n.: A way of building software that learns from examples instead of following rules written by a programmer. Shown thousands of labeled photos, for instance, a program can learn to recognize cats. and embodied, behavior-based robotics, often with a note of irony.
His critique targets GOFAI, not logic-based planning in general.
Origin
Coined by the philosopher John Haugeland in Artificial Intelligence: The Very Idea (MIT Press, 1985) to name the classical symbol-manipulation program. It spread through philosophy of mind and cognitive science and became standard shorthand in histories of AI.
Usage note
The abbreviation GOFAI is usually pronounced GO-fy. The category is loose: modern plannersautomated planning, n.: The branch of AI that works out a sequence of actions to reach a goal, such as the steps a robot must take to assemble a part, from descriptions of what each action needs and what it changes., SAT solversBoolean satisfiability problem, n.: The puzzle of deciding whether a set of true-or-false conditions can all be met at once. It is famously hard in theory, yet modern solvers routinely handle millions of conditions. and Bayesian networksBayesian network, n.: A diagram of causes and effects with probabilities attached — say, how rain and a sprinkler can each make grass wet — that lets a computer update its beliefs about hidden causes when it sees evidence. are symbolic but rarely called GOFAI, and some researchers regard the label as a caricature of a still-productive field.
Related
- symbolic AIsymbolic AI, n.: An approach to AI that writes knowledge down as human-readable symbols and rules, such as 'every bird has wings', and reasons by manipulating them step by step instead of learning patterns from data.
- physical symbol system hypothesisphysical symbol system hypothesis, n.: The 1976 claim by two AI pioneers that a machine which stores and rearranges symbols according to rules has everything needed for general intelligence, and that anything generally intelligent must be such a machine.
- expert systemexpert system, n.: A program that stores a human specialist's know-how as many if–then rules and uses them to give advice or make decisions in a narrow field, such as diagnosing infections or configuring computers.
- neats and scruffiesneats and scruffies, phr.: A joking split of AI researchers into 'neats', who want clean mathematical theories that can be proved correct, and 'scruffies', who build messy collections of tricks that simply work.
- AI winterAI winter, n.: A slump in which disappointment over AI's unmet promises leads governments and companies to pull back money and attention. Historians count two big ones: one in the 1970s and one starting in the late 1980s.
- neuro-symbolic AIneuro-symbolic AI, n.: AI that combines neural networks, which learn patterns from data, with symbolic methods, which follow explicit rules and logic, aiming for systems that both learn flexibly and reason reliably.
- connectionismconnectionism, n.: The view that minds and intelligent machines are best built from huge networks of simple, neuron-like units whose connection strengths are learned, rather than from explicit rules and symbols.
Sources
- Haugeland, J. (1985). Artificial Intelligence: The Very Idea. MIT Press.
Mentioned in
symbolic AIsymbolic AI, n.: An approach to AI that writes knowledge down as human-readable symbols and rules, such as 'every bird has wings', and reasons by manipulating them step by step instead of learning patterns from data., frame problemframe problem, n.: The difficulty of getting an AI to work out what does and does not change when something happens, without spelling out every one of the countless things that stay the same., Hubert DreyfusHubert Dreyfus, prop. n.: An American philosopher who argued from the 1960s that computers following explicit rules could never match human intelligence, which rests on bodily, intuitive know-how., physical symbol system hypothesisphysical symbol system hypothesis, n.: The 1976 claim by two AI pioneers that a machine which stores and rearranges symbols according to rules has everything needed for general intelligence, and that anything generally intelligent must be such a machine., Rodney BrooksRodney Brooks, prop. n.: An Australian-American roboticist who argued that intelligence grows out of acting in the world rather than abstract reasoning, and who co-founded the company behind the Roomba vacuum., Dreyfus's critique of AIDreyfus's critique of AI, n.: The philosopher Hubert Dreyfus's argument, from the 1960s on, that rule-based AI could never match human intelligence, because much human skill rests on bodily know-how and intuition rather than explicit rules., neats and scruffiesneats and scruffies, phr.: A joking split of AI researchers into 'neats', who want clean mathematical theories that can be proved correct, and 'scruffies', who build messy collections of tricks that simply work., SHRDLUSHRDLU, prop. n.: A program from around 1970 that let people move toy blocks in a simulated world by typing ordinary English commands and questions, and that could explain what it had done and why., subsumption architecturesubsumption architecture, n.: A way to build robot brains from stacked, reflex-like behaviors — a bottom layer that keeps clear of obstacles, others that roam or explore — where higher layers can take over from lower ones, with no central map or plan.