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The blackboard architecture is a flexible and powerful expert system framework. It represents a general approach to problem solving that is useful in many domains of applications especially in the area of intelligent control.
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.
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.
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 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.
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Blackboard is a Web-based course-management system designed to allow students and faculty to participate in classes delivered online or use online materials and activities to complement face-to-face teaching.
AI technology called machine learning today, is great at helping for taking good photos, translating languages, recognizing your friends onFacebook, delivering search results, screening out spam and many other chores.
The phrase ‘machine learning’ dates back to the middle of the last century where Arthur Samuel in 1959 defined machine learning as “the ability to learn without being explicitly programmed.”
Behavior Trees assets in Unreal Engine 4 (UE4) can be used to create artificial intelligence (AI) for non-player characters in your projects.
This guide shows how to use Behaviour Trees to set up an AI character that will patrol or chase a player.
Describes the concepts behind Behavior Trees in UE4 and how they differ from traditional Behavior Trees.