Artificial Intelligence


Aim and scope of AI. Historical data. Problem Solving. Search. Blind and informed Search. Adversarial Search. Propositional Logic. Predicate Logic. Reasoning and Resolution. Knowledge Representation. Semantic Networks. Conceptual Graphs. Machine Learning, Instance-based Learning, Decision Trees, Stochastic Learning. The Weka Machine Learning Toolkit. Expert Systems. The CLIPS Production System Language. Applications of AI.

Objectives

Aim and scope of AI. Historical data. Problem Solving. Search. Blind and informed Search.

Prerequisites

Non required

Syllabus

Aim and scope of AI. Historical data. Problem Solving. Search. Blind and informed Search. Adversarial Search. Propositional Logic. Predicate Logic. Reasoning and Resolution. Knowledge Representation. Semantic Networks. Conceptual Graphs. Machine Learning, Instance-based Learning, Decision Trees, Stochastic Learning. The Weka Machine Learning Toolkit. Expert Systems. The CLIPS Production System Language. Applications of AI.

COURSE DETAILS

Level:

Type:

Undergraduate

(A+)

Instructors: Katia Lida Kermanidis
Department: Department of Informatics
Institution: Ionian University
Subject: Computer Science, Information Technology, Telecommunications
Rights: CC - Attribution-NonCommercial-NoDerivatives

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