Pairs is an application consisting of a report represented as an HTML document, blackboard architecture that provides a shared working memory for the sequence of tasks and a control shell that coordinates tasks to be done by a variety of smart tools.
Blackboard Architectural Pattern Blackboard The Blackboard arrchitectural pattern is useful for problems for which no deterministic soluion strategies are known. In Blackboard several specialized subsystems assemble their knowledge to build a possibly partial or approximate solution. Reference page 71{98 in Buschmann F., Meunier R., Rohnert H ...
3. Blackboard Architecture The blackboard architecture is a powerful expert system architecture and model of cooperative, distributed problem solving. It can deal with large amounts of diverse, erroneous and incomplete knowledge to solve problems. The basic blackboard architecture consists of a shared data region call the blackboard, a set of independent
In software engineering, the blackboard pattern is a behavioral design pattern that provides a computational framework for the design and implementation of systems that integrate large and diverse specialized modules, and implement complex, non-deterministic control strategies.
A blackboard system consists of three components: 1) Knowledge sources (KSs); 2) Blackboard; 3) Control component. Knowledge sources are independent modules that contain the knowledge needed for problem solving.
Advantages of Blackboard Architecture Style Blackboard architecture style provides concurrency which allows knowledge sources to work in parallel. This architecture supports experimentation for hypotheses and reusability of knowledge source components.
The most well-known examples of the data-centered architecture is a database architecture, in which the common database schema is created with data definition protocol – for example, a set of related tables with fields and data types in an RDBMS.
Architectures must have both form and function and it is a good test of an architecture to measure its elegance. An architecture that is well designed will tend to be elegant and have a simplicity of form that will be obvious to those that take the time study it.
The Pipe and Filter is an architectural pattern for stream processing. It consists of one or more components called filters. These filters will transform or filter data and then pass it on via connectors called pipes.
A software architect makes important decisions regarding the software that goes on to define its overall integrity. A good software architecture helps define attributes such as performance, quality, scalability, maintainability, manageability, and usability.Jul 12, 2021
A repository architecture consists of a central data structure (often a database) and a collection of independent components which operate on the central data structure Examples of repository architectures include blackboard architectures, where a blackboard serves as communication centre for a collection of knowledge ...
Reference architecture or model provides a common vocabulary, reusable designs, and industry best practices that are used as a constraint for more concrete architectures. Typically, reference architecture includes common architecture principles, patterns, building blocks, and standards.
Architecture Style Software architecture is the high level structure used for creating software systems and is actually a step-by-step blueprint of the entire software that is to be built. The purpose of the software and its specific functionalities are defined by the software's architectural style and pattern used.Jan 24, 2022
Online Test92.Architectural styles is composed of which of the following?a.A set of component types that perform some function at run-timeb.A topological layout of these components indicating their run-time inter relationshipsc.A set of semantic constraintsd.All of the mentioned
Architectural design is a concept that focuses on components or elements of a structure. An architect is generally the one in charge of the architectural design. They work with space and elements to create a coherent and functional structure.May 23, 2018
Pairs is an application consisting of a report, represented as an HTML document; blackboard architecture that provides a shared working memory for the sequence of tasks; and a control shell that coordinates tasks to be done by a variety of smart tools.
The central concept of a model-based system is a model, a description of a device, or a system using an appropriate modeling language. The model specifies the structure, functions, and behaviors of the devices for the purposes of analysis, prediction, diagnosis, and other such procedures.
Generally, the knowledge base of a rule-based expert system consists of a set of rules of the following form: if condition1 and … and conditionm are true then conclusion1 and … and conclusionn. Each rule contains one or more conditions and one or more conclusions or actions. MYCIN is a classical rule-based system.
In the field of expert system, research methods for handling uncertainty include certainty factor approach, the Bayesian approach, fuzzy logic, and the belief theory. In the certainty factor approach certainty factors are associated with given data, indicating their degree of certainty.
The Expert System architecture consists of a knowledge base and an inference engine ( Fig. 4 ). Its knowledge is generally represented in terms of rules. Rules represent domain knowledge in an ‘if-then-else’ format and they can be written in different programming languages like C, LISP, and OWL. For example, in the CLIPS expert system used by Siemens, rules are written in OWL 2 language in the format of concept-ontology and instance-ontology [ 56 ]. In some cases, frames are also used to represent the knowledge in expert systems. Frames are used to represent the stereotyped knowledge as a collection of attributes and their associated values. An example is the meteorological vehicle system, wherein the expert system for fault diagnosis is built using object-frame structure, with the frame being a collection of state-object, test-object, rule-object, and repair-object [ 57 ]. Most Expert systems employ Rule-Based Reasoning (RBR) methodology to solve their problem. The RBR is executed in the following two ways: i) Forward Chaining, and ii) Backward Chaining. Forward Chaining starts with the initial state of facts and applies the rules until the endpoint is reached. Backward Chaining starts from a hypothesis and looks for rules that will allow the hypothesis to be proven. In other words, it starts with an effect and looks for the possible root causes that could lead to that effect. Forward Chaining is data driven whereas Backward Chaining is goal driven [ 58 ].
The CBR has its knowledge derived from the historical cases. It has a simple framework consisting of four phases: i) retrieve, ii) reuse, iii) revise, and iv) retain ( Fig. 6 ). In the retrieval phase, knowledge in the database (case repository) in the form of previous experiences and histories (cases) related to the application are searched for. These old cases are then retrieved based on their index and interpreted for the current problem. In the reuse phase, the old cases are adapted to the present situation in order to find the solution. Evaluation of the new cases is carried out and solutions suggested in the revise phase and the new cases are then added to the case repository for future learning, as a part of the retain phase [ 64 ]. One of the examples of CBR application is Intelligent Systems for Aircraft Conflict Resolution (ISAC) [ 65] which was developed to help the decision-making process of aircraft controllers to resolve the conflicts between aircraft. CBR is one of the most commonly used reasoning systems, as its architecture has the capability of accommodating any advanced algorithms, mainly text processing techniques. Moreover, CBR does not require prior knowledge about the system as it solely depends on past experience. Since the CBR involves learning as a part of its methodology enabling knowledge evolution, the CBR can evolve and become expert in the domain, thus having the potential of becoming the future expert systems [ 66 ]. This is an advantage over the other frameworks since the other reasoning systems require maintenance time for updating the knowledge base. Nonetheless, the CBR system is computationally demanding when compared with the PRS and simple rule-based Expert Systems.