INTELLIGENT SOFTWARE - Knowledge Representation, Intelligent Tutoring Systems

IPLI draws from experience and training in advanced software and techniques such as Artificial Intelligence, Knowledge-Based Systems, and Object Oriented Programming. Such experience and expertise affords deep insight which transcends all areas of computation and systems design, and extends into theory of learning sciences and education.When combined with advanced programming methods, this insight can be used to create better-organized, more "intelligent" software, and complex systems.

Artificial Intelligence (AI) is fundamentally the study of abstracted knowledge, logic, and its manipulation in computers bringing together areas of Cognitive Science, Computation, and Theoretical Mathematics. It provides an intimate and useful familiarity with organization and representation of knowledge and logic underlying software design, systems, and human reasoning. For example, simply understanding a problem and solution in terms of required abstract knowledge, and behavior, assists in an engineering process freeing thinking from limitations of underlying platforms and constraints. Also, programming methods and principles borrowed from Knowledge Based Systems and Artificial Intelligence, ranging from simple knowledge and logic abstraction, to rule based components, can be used to build software along a spectrum of sophistication. These methods or principles may be used to create more "intelligent" or flexible software, or "complex systems" comprised of distributed logic or multiple technologies.

IPLI draws from experience and research in advanced software areas such as knowledge representation, pattern recognition, and intelligent tutoring systems. An understanding of principles and methods in these areas allows deeper insight into potential solutions and the potential to create more versatile or useful applications across a variety of domains.

This initiative is both an applied domain and area of technical expertise which can be combined with other initiatives. Examples of IPLI backgroundresearch expereince and IPLI applied solutions include the following:

Experience in research which may contribute to IPLI "Intelligent" Software and Complex System Development:
Graphical Knowledge Manipulation Knowledge Representation Knowledge Based Systems Expert Systems	Machine Learning Intelligent Tutoring Systems Pattern Recognition Systems Rule Base Augmented Simulation	Hybrid Multimedia - Client Server Applications Client/Server Distributed Logic Pseudo NLP Simulation Interface
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