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    Production System: Fundamentals and Applications
    Production System: Fundamentals and Applications
    Production System: Fundamentals and Applications
    Ebook93 pages1 hourArtificial Intelligence

    Production System: Fundamentals and Applications

    By Fouad Sabry

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    About this ebook

    What Is Production System


    A "production system" is a computer program that is often used to produce some form of artificial intelligence. This type of software consists largely of a collection of rules regarding behavior, but it also includes the mechanism necessary to follow those rules when the system reacts to different situations of the world. These rules, which are also known as products, are an example of a fundamental representation that can be helpful in automated planning, expert systems, and action selection.


    How You Will Benefit


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


    Chapter 1: Production System in Computer Science


    Chapter 2: Constraint Handling Rules


    Chapter 3: CLIPS


    Chapter 4: Drools


    Chapter 5: ILOG


    Chapter 6: Jess Programming Language


    Chapter 7: Lisp-Based Intelligent Software Agents


    Chapter 8: OpenL Tablets


    Chapter 9: Prolog


    Chapter 10: Soar Cognitive Architecture


    (II) Answering the public top questions about production system.


    (III) Real world examples for the usage of production system in many fields.


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

    LanguageEnglish
    PublisherOne Billion Knowledgeable
    Release dateJun 29, 2023
    Production System: Fundamentals and Applications

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      Book preview

      Production System - Fouad Sabry

      Chapter 1: Production system (computer science)

      A computer program is referred to as a production system (or a production rule system) when it is used to provide some form of artificial intelligence. This type of program consists primarily of a set of rules about behavior, but it also includes the mechanism necessary to follow those rules as the system reacts to states in the world. These rules, which are also known as products, are a fundamental representation that may be helpful in automated planning, expert systems, and action selection.

      A sensory precondition (also known as a IF statement) is the first component of a production, followed by an action (or THEN). It is claimed that a production has been triggered when the precondition of the production meets the state that the world is in at the time. When the activity of a production is carried out, we say that the production has fired. A database, sometimes known as working memory, is part of a production system. Its purpose is to store information on the current state or knowledge, and it also includes an interpreter for rules. When more than one production is triggered at the same time, the rule interpreter is required to offer a method for prioritizing the productions.

      Rule interpreters will often carry out a forward chaining algorithm when choosing which productions to carry out in order to achieve the objectives at hand. This may include bringing the system's data or beliefs up to date. The left-hand side, often known as the LHS, of each rule is used to compare the current state of the working memory with the conditional section of the rule.

      There is an assumption that any triggered circumstances should be performed in data-oriented or idealized production systems. The subsequent actions (right-hand side or RHS) will update the agent's knowledge by deleting or adding data to the working memory. The operation of the system comes to a halt when one of the following conditions is met: the user interrupts the forward chaining loop; a predetermined number of cycles have been completed; a halt RHS instruction is carried out; or there are no more rules with LHSs that are true.

      Real-time and expert systems, on the other hand, are often forced to pick between products that are incompatible with one another. This is because actions cost time, and hence only one action may be done or, in the case of an expert system, advised. In these kinds of computer systems, the rule interpreter, also known as the inference engine, goes through a cycle consisting of two steps. First, it compares the production rules with the database. Then, it decides which of the matched rules should be applied and carries out the actions that have been chosen.

      The degree to which circumstances in production rules are able to represent meaning might differ from production system to production system. Accordingly, the pattern matching algorithm that collects production rules with matched conditions can range from the naive—trying all rules in sequence, stopping at the first match—to the optimized, in which rules are compiled into a network of inter-related conditions. The naive algorithm collects production rules with matched conditions and stops at the first match.

      The latter is shown by the RETE algorithm, which was invented in 1974 by Charles L. Forgy. It is used in a series of production systems known as OPS, which were first developed at Carnegie Mellon University and culminated in OPS5 in the early 1980s. It is possible to consider OPS5 to be a fully-fledged programming language for use in production system programming.

      The production rules that are ultimately chosen to be carried out, or fired, by a system might also vary from one system to the next. The group of rules that were produced as a consequence of the prior matching algorithm is referred to as the conflict set, and the method of rule selection is also referred to as a conflict resolution technique.

      Again, these strategies can range from being extremely simple, such as use the order in which production rules were written, to being extremely complex, such as sort the conflict set according to the times at which production rules were previously fired, or according to the extent of the modifications induced by their RHSs. No matter whether technique of dispute resolution is chosen to be applied, the process is very essential to ensuring that the production system is both effective and accurate. Some systems will just trigger all products that are a match.

      The use of production systems may range anywhere from the utilization of simple string rewriting rules to the modeling of human cognitive processes, from term rewriting and reduction systems to expert systems.

      The following is an example of a set of production rules for reversing a string derived from an alphabet that does not include the characters $ and *. (which are used as marker symbols).

      P1: $$ -> *

      P2: *$ -> *

      P3: *x -> x*

      P4: * -> null & halt

      P5: $xy -> y$x

      P6: null

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