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    Blackboard System: Fundamentals and Applications
    Blackboard System: Fundamentals and Applications
    Blackboard System: Fundamentals and Applications
    Ebook126 pages1 hourArtificial Intelligence

    Blackboard System: Fundamentals and Applications

    By Fouad Sabry

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    About this ebook

    What Is Blackboard System


    A blackboard system is an artificial intelligence technique that is based on the blackboard architectural model. In this paradigm, a common knowledge base, also known as the "blackboard," is iteratively updated by a diverse set of expert knowledge sources, beginning with a problem specification and ending with a solution. A blackboard system is also known as a blackboard system. If a knowledge source's internal constraints are satisfied by the current state of the blackboard, then that knowledge source contributes a partial solution to the blackboard. The problem is ultimately solved as a result of the combined efforts of the specialists. The blackboard model was at first conceived as a method for dealing with difficult, ill-defined situations in which the solution is equal to the total of the problem's components.


    How You Will Benefit


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


    Chapter 1: Blackboard System


    Chapter 2: Artificial Intelligence


    Chapter 3: Expert System


    Chapter 4: Knowledge Representation and Reasoning


    Chapter 5: Distributed Artificial Intelligence


    Chapter 6: Symbolic Artificial Intelligence


    Chapter 7: Collaborative Intelligence


    Chapter 8: Multi-Agent System


    Chapter 9: Knowledge-Based Systems


    Chapter 10: Outline of Artificial Intelligence


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


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


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

    LanguageEnglish
    PublisherOne Billion Knowledgeable
    Release dateJun 24, 2023
    Blackboard System: Fundamentals and Applications

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      Book preview

      Blackboard System - Fouad Sabry

      Chapter 1: Blackboard system

      A blackboard system is an artificial intelligence strategy based on the blackboard architectural model, where a common knowledge base, the blackboard, is updated iteratively by a variety of specialized knowledge sources, beginning with a problem definition and ending with a solution. When its internal constraints meet the blackboard state, each knowledge source updates the blackboard with a partial solution. In this manner, the experts collaborate to find a solution to the issue. The initial purpose of the blackboard model was to address complex, ill-defined situations where the whole is greater than the sum of its parts.

      The story that follows offers a straightforward metaphor that sheds some light on how a blackboard operates:

      A giant blackboard is in the center of the room where a number of experts are seated. The chalkboard serves as the setting for their collaborative brainstorming session as they work as a team to find a solution to a problem.

      When the problem specifications are printed on the whiteboard, the session officially starts. Each specialist keeps an eye on the whiteboard in anticipation of a chance to contribute their knowledge to the evolving solution. The second specialist records their contribution on the chalkboard when something is written that enables another specialist to apply their expertise, hopefully allowing other specialists to do the same. Until the issue is resolved, this procedure of adding comments to the board will continue.

      There are three main parts to a blackboard system application.

      Knowledge sources are the software specialized modules (KSs). Each knowledge source delivers the unique expertise required by the application, much like the human specialists at a blackboard.

      The blackboard, a shared database of issues, imperfect solutions, ideas, and user-contributed knowledge. You might think of the blackboard as a dynamic library of solutions to the current issue that have just been published by other information sources.

      The system's problem-solving activity is governed by the control shell. KSs require a mechanism to organize their use in the most efficient and cogent way, just as the eager human specialists need a moderator to keep them from trampling each other in a wild rush to take the chalk. The control shell in a blackboard system provides this.

      The focal point of a multi-agent system is a blackboard system. It is used to explain how the world functions as a platform for agent communication. In order to implement a blackboard in a computer program, facts must be stored in a machine-readable format. A SQL database is one method of doing this, and another choice is the Learnable Task Modeling Language (LTML). The LTML planning language uses PDDL-like syntax but has extras like control structures and OWL-S models.

      Here is a brief illustration: A process in a computer game is being carried out by a human user. The player interacts with the game engine by pressing a few buttons. A plan trace is established while the player engages with the game. That implies that a logfile contains the user's actions. The logfile is changed into a syntax that is machine readable and enhanced with semantic characteristics. The outcome is a text file using LTML syntax that is shown on the whiteboard. The LTML syntax can be parsed by agents, which are computer programs in the Blackboard system.

      BB1 and GBB, two well-known early Blackboard systems, are discussed here before moving on to more contemporary implementations and applications.

      Blackboard architecture BB1 Roth & Hayes, Inc. Roth discovered that, in contrast to the predominately top-down planners employed at the time, human planning was more closely characterized as an opportunistic process:

      Our understanding of planning is somewhat different from successive-refinement models, albeit it is not incompatible. We both operate on the presumption that planning procedures take place in a two-dimensional realm with dimensions for time and abstraction. We do, however, believe that most planning is opportunistic in nature. In other words, the planner's present choices and observations suggest various options for plan creation at each stage of the process. The planner's decisions after that take use of certain opportunities. These decision-sequences can occasionally take an ordered course and result in the above-described clean top-down expansion. Nevertheless, some conclusions and findings can also point to less systematic chances for plan development.

      One of BB1's important innovations was how it used the same gradual, opportunistic blackboard approach of problem-solving that was used to address domain issues to apply this opportunistic planning model to its own control. Then, planning and problem-solving could be monitored to see if they were progressing as intended or had stalled using meta-level reasoning and control knowledge sources. If stalled, BB1 may move from one tactic to another as circumstances, like the goals being taken into account or the amount of time left, altered. The linguistic framework for BB1 specified a specific method for resolving configuration issues. It was used in a variety of fields, including planning construction sites. The method for solving the problem involved gradually putting together a solution by including new items and constraints. Short English-like commands or sentences that define preferred actions, events that cause KSes to run, preconditions for running KS actions, and obviation requirements for discarding KS actions that are no longer necessary make up the actions in the ACCORD language framework.

      One of GBB's control shells, GBB, implements BB1's control strategy while bringing about efficiency gains.

      Douglas Hofstadter's Copycat and Numbo projects, the Hearsay II voice recognition system, and other early academic blackboard systems are also well-known.

      A few more current instances of real-world applications in use include:

      The RADARSAT-1 Mission Control System's PLAN component, Modern Bayesian machine learning environments have been built with systems resembling blackboards that use agents to add and remove Bayesian network nodes. The heuristics can take on more strict probability interpretations in these Bayesian Blackboard systems as proposals and acceptances in Metropolis Hastings sampling through the space of potential structures.

      {End Chapter 1}

      Chapter 2: Artificial intelligence

      As contrast to the natural intelligence exhibited by animals, including humans, artificial intelligence (AI) refers to the intelligence demonstrated by robots. Research in artificial intelligence (AI) has been described as the area of study of intelligent agents, which refers to any system that senses its surroundings and performs actions that optimize its possibility of attaining its objectives. In other words, AI research is a discipline that studies intelligent agents. The term AI impact refers to the process by which activities that were formerly thought to need intelligence but are no longer included in the concept of artificial intelligence as technology advances. AI researchers have adapted and incorporated a broad variety of approaches for addressing issues, including search and mathematical optimization, formal logic, artificial neural networks, and methods based on statistics, probability, and economics, in order to tackle these difficulties. Computer science, psychology, linguistics, philosophy, and a great many other academic disciplines all contribute to the development of AI.

      The theory that human intellect can be so accurately characterized that a computer may be constructed to imitate it was the guiding principle behind the establishment of this discipline. This sparked philosophical debates concerning the mind and the ethical implications of imbuing artificial organisms with intellect comparable to that of humans; these are topics that have been investigated by myth, literature, and philosophy ever since antiquity.

      In ancient times, artificial creatures with artificial intelligence were used in various narrative devices.

      and are often seen in works of literature, as in Mary Shelley's Frankenstein or Karel Čapek's R.U.R.

      The formal design for Turing-complete "artificial

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