Automated Reasoning: Fundamentals and Applications

By Fouad Sabry

What Is Automated Reasoning

Understanding many facets of reasoning is the focus of the subfield of computer science known as automated reasoning. This subfield is particularly important in the fields of knowledge representation and reasoning as well as metalogic. The study of automated reasoning contributes to the production of computer programs that enable computers to reason automatically, or nearly automatically. Automated reasoning is sometimes categorized as a subfield of artificial intelligence; nevertheless, it also has linkages to theoretical computer science as well as philosophy.

How You Will Benefit

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

Chapter 1: Automated reasoning

Chapter 2: Applications of artificial intelligence

Chapter 3: Abductive reasoning

Chapter 4: Automated theorem proving

Chapter 5: Commonsense reasoning

Chapter 6: Case-based reasoning

Chapter 7: Reasoning system

Chapter 8: Program analysis

Chapter 9: Inference engine

Chapter 10: Automated machine learning

(II) Answering the public top questions about automated reasoning.

(III) Real world examples for the usage of automated reasoning in many fields.

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

• Language: English
• Publisher: One Billion Knowledgeable
• Release date: Jul 6, 2023

Book preview

Chapter 1: Automated reasoning

Understanding many facets of reasoning is the focus of the subfield of computer science known as automated reasoning. This subfield is particularly important in the fields of knowledge representation and reasoning as well as metalogic. The study of automated reasoning contributes to the development of computer programs that enable computers to think automatically, or almost automatically. Although automated reasoning is categorized as a subfield of artificial intelligence, it also has ties to the theoretical side of computer science and the philosophical side of thought.

The subfields of automated reasoning that are the farthest along in their development are automated theorem proving (together with the less automated but more pragmatic subfield of interactive theorem proving) and automated proof checking (viewed as guaranteed correct reasoning under fixed assumptions). There has also been a significant amount of study done in the area of reasoning by analogy employing induction and abduction. is an example of a more specialized kind of automated argumentation system than just an automated theorem prover.

The classical logics and calculi, fuzzy logic, Bayesian inference, reasoning with maximum entropy, and a large number of less formal ad hoc approaches are some of the tools and techniques that are used in automated reasoning.

The growth of formal logic was an important contributor to the study of automated reasoning, which in turn paved the way for the creation of artificial intelligence. A proof is considered to be formal if it can be shown that every logical inference has been verified back to the axioms that underlie mathematics. Without a single exception, each and every one of the intermediate logical stages is provided. There is no consideration given to intuitive understanding, despite the fact that the transition from intuition to logic is a matter of routine. Because of this, a formal proof is easier to follow and less likely to include any logical flaws.

Alfred North Whitehead and Bertrand Russell's work, Principia Mathematica, is widely regarded as a seminal contribution to the field of formal logic. The book Principia Mathematica, which also goes by the name Principles of Mathematics, was produced with the intention of deriving all or part of the mathematical statements using symbolic logic. The first edition of Principia Mathematica was released in three separate volumes in 1910, 1912, and 1913 respectively. The computer program, in addition to establishing the theorems, came up with a proof for one of the theorems that was more sophisticated than the evidence that Whitehead and Russell had presented. Following a failed effort to publish their findings, Newell, Shaw, and Herbert revealed their findings in their paper titled The Next Advance in Operation Research, which was released in the year 1958:

There are now machines in the world that are capable of thinking, learning, and creating new things. In addition to this, their capability to do these tasks is going to swiftly improve until (in the not too distant future), the scope of issues that they are able to solve will be on par with the issues that have been tackled by the human mind in the past.

Some Illustrations of Formal Proofs

Theorem Prover Using the Boyer-Moore Equation (NQTHM)

John McCarthy and Woody Bledsoe were both significant contributors to the creation of NQTHM. This was a completely automated theorem prover that was constructed using Pure Lisp. Its development began in 1971 in Edinburgh, Scotland. The primary components of NQTHM were as follows::

the implementation of functioning logic using Lisp.

the adherence to a general concept of definition when dealing with complete recursive functions.

the significant amount of rewriting, as well as the usage of symbolic assessment,.

a failed attempt at symbolic assessment that is based on an induction heuristic.

HOL Light

The logical underpinning of HOL Light is intended to be straightforward and clear, while its implementation is intended to be clutter-free. HOL Light is written in OCaml. In essence, it is a new proof helper for traditional higher order logic.

Coq

Coq is another automated proof aid that was developed in France. It has the capability of automatically extracting executable programs from specifications in the form of either Objective CAML or Haskell source code. Formalization of properties, programs, and proofs occurs in the same language, which is referred to as the Calculus of Inductive Constructions (CIC).

The most prevalent use of automated reasoning has been in the construction of automated theorem provers. However, theorem provers often need some human assistance in order to be successful, and as a result, they more typically fall under the category of proof helpers. In a few instances, such provers have devised novel strategies for demonstrating a theorem's validity. One band that exemplifies this well is Logic Theorist. The computer algorithm devised a proof for one of the theorems in Principia Mathematica that was more effective (used fewer steps) than the proof that Whitehead and Russell had supplied for it. Automated reasoning programs are now being used to tackle an increasing number of issues in formal logic, mathematics and computer science, logic programming, software and hardware verification, circuit design, and a variety of other fields. This kind of issue may be found in the TPTP (Sutcliffe and Suttner 1998), which is a library that is regularly updated with new examples. In addition, there is a competition among automated theorem provers that takes place annually at the CADE conference (Pelletier, Sutcliffe, and Suttner 2002). The questions that are used for the competition are chosen from the TPTP collection.

{End Chapter 1}

Chapter 2: Applications of artificial intelligence

Artificial intelligence, sometimes known as AI, has been put to use in a number of applications in both the business world and the academic world to solve various challenges. Artificial intelligence, much like electricity and computers, is a type of technology that may be used for a wide variety of purposes. It has been put to use in a variety of industries, including translation of languages, recognition of images, calculation of credit scores, online business, and others.

The grade or preference that a user would assign to an item can be inferred through the use of a recommendation system.

In addition, machine learning is utilized in Web feeds, such as in the selection process for which postings are displayed in a user's social network feed.

Artificial intelligence is being used to target online adverts to people who are most likely to click on them or engage with them. It is also used to improve the amount of time spent on a website by the viewer by selecting information that is appealing to them. Based on the customers' digital footprints, it is able to forecast or generalize the behavior of the customers.

Intelligent personal assistants make use of artificial intelligence in order to comprehend a wide variety of natural language requests in addition to