Qualification Problem: Fundamentals and Applications

By Fouad Sabry

What Is Qualification Problem

In artificial intelligence and philosophy, the qualifying problem refers to the impossibility of enumerating all of the preconditions that must be met for a real-world action to have the effect it was intended for it to have. The question could be phrased as one of how to handle the obstacles that stand in the way of my getting the result I want. It has a strong connection to the frame problem and stands in contrast to the ramification side of that problem. The following is a motivating example provided by John McCarthy, in which it is hard to enumerate all of the events that may prevent a robot from completing its usual function:"[T]he use of a boat to successfully cross a river needs, if the boat is a rowboat, that the oars and rowlocks be present and unbroken, and that they fit each other. If the boat is not a rowboat, then the use of the boat will not be successful. Anyone will be able to think of other needs that have not yet been stated, despite the fact that the rules for operating a rowboat can have many other conditions added to them, which makes it practically difficult to implement the regulations.

How You Will Benefit

(I) Insights, and validations about the following topics:

Chapter 1: Qualification Problem

Chapter 2: John McCarthy (computer scientist)

Chapter 3: Logic Programming

Chapter 4: Symbolic Artificial Intelligence

Chapter 5: Commonsense Reasoning

Chapter 6: Cyc

Chapter 7: Douglas Lenat

Chapter 8: Commonsense Knowledge (Artificial Intelligence)

Chapter 9: Belief Revision

Chapter 10: Frame Problem

(II) Answering the public top questions about qualification problem.

(III) Real world examples for the usage of qualification problem in many fields.

(IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of qualification problem' technologies.

Who This Book Is For

Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of qualification problem.

• Language: English
• Publisher: One Billion Knowledgeable
• Release date: Jun 26, 2023

Book preview

Chapter 1: Qualification problem

The qualifying problem is a concern with the inability of stating all the prerequisites necessary for a real-world action to have its intended effect in philosophy and AI (particularly knowledge-based systems). where it is hard to list every scenario that could prohibit a robot from carrying out its normal function:

If the boat is a rowboat, the oars and rowlocks must be present, undamaged, and fitted to each other for the crossing to be successful. Anyone will be able to come up with extra needs that haven't yet been specified, even after many additional requirements have been introduced, making it nearly hard to implement the rules for using a rowboat.

{End Chapter 1}

Chapter 2: John McCarthy (computer scientist)

John McCarthy was an American computer scientist and cognitive scientist. He was born on September 4, 1927, and passed away on October 24, 2011. He was a pioneer in the field of artificial intelligence, and is considered one of its pioneers. He promoted time-sharing, pioneered garbage collection, and was a co-author on the paper that first used the phrase artificial intelligence (AI). He also established the computer language family Lisp, had a substantial effect on the design of the language ALGOL, and developed the language.

McCarthy worked at Stanford University for the vast majority of his career. the National Medal of Science of the United States of America, as well as the Kyoto Prize.

John McCarthy was born in Boston, Massachusetts, on September 4, 1927, to parents who had immigrated to the United States from Ireland and Lithuania, respectively. McCarthy got admitted into Caltech in the year 1944.

McCarthy shown an early ability for mathematics, and when he was still in his teens, he taught himself college mathematics by reading the textbooks that were being used at the California Institute of Technology, which was located nearby (Caltech). As a direct consequence of this, he was exempt from the prerequisite coursework for the first two years of mathematics at Caltech. McCarthy was kicked out of Caltech for not attending the required number of days of physical education classes.

It was a talk by John von Neumann that he heard when he was a student at Caltech that served as the impetus for his subsequent work.

After completing his graduate studies at Caltech, McCarthy transferred to Princeton University to continue his education. In 1951, he successfully defended his doctoral dissertation at Princeton University, which was titled Projection operators and partial differential equations, and was directed by Donald C. Spencer. As a result, he was awarded a doctorate in mathematics from that institution.

McCarthy joined the faculty of Dartmouth College in 1955 as an assistant professor, having previously held adjunct positions at Princeton University and Stanford University.

After waiting another year, McCarthy became a research fellow at the Massachusetts Institute of Technology (MIT) in the fall of 1956. By the time he had completed all of his studies at MIT, his former pupils had already begun to refer to him fondly as Uncle John..

McCarthy was promoted to the position of full professor at Stanford in 1962, and he stayed there until his retirement in the year 2000.

McCarthy was an advocate for the study of mathematics, such as lambda calculus, and an inventor of logics for developing artificial intelligence with more common sense.

In the field of artificial intelligence, John McCarthy is considered to be one of the founding fathers, along with Alan Turing, Marvin Minsky, Allen Newell, and Herbert A. Simon. McCarthy, Minsky, Nathaniel Rochester, and Claude E. Shannon first used the phrase artificial intelligence in a proposal that they made for the renowned Dartmouth conference in the summer of 1956. Claude E. Shannon also contributed to the development of the word. The area of AI was officially launched during this conference. (Later on, Minsky joined McCarthy at MIT in the year 1959.)

1958 was the year that he first suggested the idea of the advice taker, which would later inspire work on question-answering and logic programming.

McCarthy made the discovery that simple recursive functions could be extended to compute using symbolic expressions during the latter half of the 1950s, which led to the creation of the programming language known as Lisp. This important study on functional programming also introduced the lambda notation, which was derived from the syntax of lambda calculus and served as the foundation upon which other languages, such as Scheme, founded their semantics. After its first release in 1960, Lisp quickly established itself as the go-to programming language for artificial intelligence applications.

McCarthy was a member of an ad hoc committee on Languages that was established by the Association for Computing Machinery in 1958. This group eventually became a component of the team that produced ALGOL 60. In August of 1959, he put out the idea of using recursion and conditional expressions, both of which were eventually included into ALGOL.

When he was at MIT, he contributed to the impetus behind the development of Project MAC, and when he was at Stanford University, he assisted in the establishment of the Stanford AI Laboratory, which was a friendly competition to Project MAC for a number of years.

McCarthy was a significant contributor to the development of three of the very early time-sharing systems (Compatible Time-Sharing System, BBN Time-Sharing System, and Dartmouth Time Sharing System). Lester Earnest, one of his colleagues, was quoted as saying this to the Los Angeles Times:

If John hadn't been the one to pioneer the creation of time-sharing systems, the Internet probably would not have come into existence nearly as quickly as it did. We continually coming up with new titles for the practice of time-sharing. It was eventually given the name servers... These days, we refer to it as cloud computing. That amounts to nothing more than time-sharing. It all began with John.

— Woo, Elaine

In a speech he delivered in 1961 to mark the 100th anniversary of the founding of the Massachusetts Institute of Technology (MIT), he is credited with being the first person to publicly propose the concept of utility computing. He hypothesized that computer time-sharing technology could one day lead to a future in which computing power and even particular applications could be sold using the utility business model (like water or electricity). The concept of a computer or information utility was extremely fashionable in the late 1960s, but by the middle of the 1990s, it had fallen out of favor. However, the concept has been making a comeback in several guises since the year 2000. (see application service provider, grid computing, and cloud computing).

In 1966, McCarthy and his team at Stanford built a computer program that was used to play a series of chess games with equivalents in the Soviet Union; McCarthy's team was victorious in two of the games and tied in two of the games. McCarthy's team was victorious in two of the games (see Kotok-McCarthy).

McCarthy created the circumscription approach of non-monotonic thinking between the years of 1978 and 1986.

It is believed that he came up with the concept of the space fountain in 1982. A space fountain is a form of tower that extends into space and is maintained upright by the outward force of a stream of pellets driven from Earth along a sort of conveyor belt that returns the pellets to Earth. The conveyor belt would move the payloads in an upward direction.

McCarthy would often provide insightful comments on current events on various