Symbolic AI after GOFAI and confusions caused by viewing symbolic AI as only GOFAI
Although the term GOFAI encompasses only a small part of symbolic AI, prominent in the 1980s, contemporary critics of symbolic AI sometimes use GOFAI as a synonym for it. This conflation of terms can lead to conclusions that symbolic AI research ended in the 1980s and avoided machine learning. Since both conclusions are false and important to correct, we address them below.The 1980s GOFAI version of symbolic AI characterized by production rules and expert systems
During the Second AI Summer, i.e., the expert systems boom of the 1980s, production-rule systems requiring knowledge engineering were used to implement expert systems. Knowledge engineering required working with subject matter experts to model task knowledge as rules. At the time, rules were hand-authored by knowledge engineers or the subject matter experts. GOFAI correctly describes this approach. Haugeland and Dreyfus also correctly pointed out various limitations, discussed in later sections. The Second AI Winter occurred after the expert systems andSymbolic AI after GOFAI
Symbolic AI continued, albeit with reduced funding. It redirected focus to address limitations in handling uncertainty, using statistical AI; and to speed knowledge acquisition, with symbolic approaches to machine learning. Work inProblems when current symbolic AI is viewed as GOFAI
Using GOFAI as a synonym for current symbolic AI leads to erroneous conclusions and confusion. Garcez and Lamb provide an example:Turing award winnerThe key points above are that symbolic AI research has long since moved beyond GOFAI, research continues, and GOFAI no longer describes it. Further, there are symbolic learning approaches to machine learning, such as inductive logic programming andJudea Pearl Judea Pearl (born September 4, 1936) is an Israeli-American computer scientist and philosopher, best known for championing the probabilistic approach to artificial intelligence and the development of Bayesian networks (see the article on belief ...offers a critique of machine learning which, unfortunately, conflates the termsmachine learning Machine learning (ML) is a field of inquiry devoted to understanding and building methods that 'learn', that is, methods that leverage data to improve performance on some set of tasks. It is seen as a part of artificial intelligence. Machine ...anddeep learning Deep learning (also known as deep structured learning) is part of a broader family of machine learning methods based on artificial neural networks with representation learning. Learning can be supervised, semi-supervised or unsupervised. .... Similarly, when Geoffrey Hinton refers to symbolic AI, the connotation of the term tends to be that of expert systems dispossessed of any ability to learn. The use of the terminology is in need of clarification.Machine learning Machine learning (ML) is a field of inquiry devoted to understanding and building methods that 'learn', that is, methods that leverage data to improve performance on some set of tasks. It is seen as a part of artificial intelligence. Machine ...is not confined toassociation rule mining Association rule learning is a rule-based machine learning method for discovering interesting relations between variables in large databases. It is intended to identify strong rules discovered in databases using some measures of interestingness.Pi ..., c.f. the body of work on symbolic ML achine learningand relational learning (the differences to deep learning being the choice of representation, localist logical rather than distributed, and the non-use of gradient-based learning algorithms). Equally, symbolic AI is not just about production rules written by hand. A proper definition of AI concernsknowledge representation and reasoning Knowledge representation and reasoning (KRR, KR&R, KR²) is the field of artificial intelligence (AI) dedicated to representing information about the world in a form that a computer system can use to solve complex tasks such as diagnosing a medic ..., autonomousmulti-agent systems A multi-agent system (MAS or "self-organized system") is a computerized system composed of multiple interacting intelligent agents.Hu, J.; Bhowmick, P.; Jang, I.; Arvin, F.; Lanzon, A.,A Decentralized Cluster Formation Containment Framework fo ...,planning Planning is the process of thinking regarding the activities required to achieve a desired goal. Planning is based on foresight, the fundamental capacity for mental time travel. The evolution of forethought, the capacity to think ahead, is c ...andargumentation Argumentation theory, or argumentation, is the interdisciplinary study of how conclusions can be supported or undermined by premises through logical reasoning. With historical origins in logic, dialectic, and rhetoric, argumentation theory, incl ..., as well as learning.
The GOFAI critique of rule-based agents
GOFAI, the rule-based approach of 1980s symbolic AI, was attacked by philosophers such asThe position they criticize came to be called "Good Old-Fashioned Al," or GOFAI, a term coined by Haugeland (1985). GOFAI is supposed to claim that all intelligent behavior can be captured by a system that reasons logically from a set of facts and rules describing the domain. It therefore corresponds to the simplest logical agent described in Chapter 7. Dreyfus is correct in saying that logical agents are vulnerable to theIn other words, GOFAI restricts its view of agents to those controlled by logical rules. In contrast to this view, symbolic AI also includes non-monotonic logic,qualification problem In philosophy and AI (especially, knowledge-based systems), the qualification problem is concerned with the impossibility of listing ''all'' the preconditions required for a real-world action to have its intended effect. It might be posed as ''h .... As we saw in Chapter 13, probabilistic reasoning systems are more appropriate for open-ended domains. The Dreyfus critique therefore is not addressed against computers per se, but rather against one particular way of programming them. It is reasonable to suppose, however, that a book called ''What First-Order Logical Rule-Based Systems Without Learning Can't Do'' might have had less impact.
The GOFAI critique of disembodied agents
Russell and Norvig do not reject all of Dreyfus’s arguments, they accept his strongest argument, one that applies to all disembodied AIs, whatever their approach:One of Dreyfus's strongest arguments is for situated agents rather than disembodied logical inference engines. An agent whose understanding of "dog" comes only from a limited set of logical sentences such as "Dog(x) ⇒ Mammal(x)" is at a disadvantage compared to an agent that has watched dogs run, has played fetch with them, and has been licked by one. As philosopherAndy Clark Andy Clark, (born 1957) is a British philosopher who is Professor of Cognitive Philosophy at the University of Sussex. Prior to this, he was at professor of philosophy and Chair in Logic and Metaphysics at the University of Edinburgh in ...(1998) says, "Biological brains are first and foremost the control systems for biological bodies. Biological bodies move and act in rich real-world surroundings: According toClark Clark is an English language surname, ultimately derived from the Latin language, Latin with historical links to England, Scotland, and Ireland ''clericus'' meaning "scribe", "secretary" or a scholar within a religious order, referring to someone ..., we are "good at frisbee, bad at logic." Theembodied cognition Embodied cognition is the theory that many features of cognition, whether human or otherwise, are shaped by aspects of an organism's entire body. Sensory and motor systems are seen as fundamentally integrated with cognitive processing. The cognit ...approach claims that it makes no sense to consider the brain separately: cognition takes place within a body, which is embedded in an environment. We need to study the system as a whole; the brain's functioning exploits regularities in its environment, including the rest of its body. Under theembodied cognition Embodied cognition is the theory that many features of cognition, whether human or otherwise, are shaped by aspects of an organism's entire body. Sensory and motor systems are seen as fundamentally integrated with cognitive processing. The cognit ...approach, robotics, vision, and other sensors become central, not peripheral.
Citations
References
* * * * * * * * * * * * * * {{Cite journal, doi = 10.1093/mind/LIX.236.433, issn = 0026-4423, volume = LIX, issue = 236, pages = 433–460, last = Turing, first = A. M., title = I.—Computing Machinery and Intelligence, journal = Mind, accessdate = 2022-09-14, date = 1950, url = https://doi.org/10.1093/mind/LIX.236.433 zh-yue:GOFAI Terms in science and technology Artificial intelligence