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Artificial Intelligence

Angelo MARCELLI Artificial Intelligence

0622700020
DIPARTIMENTO DI INGEGNERIA DELL'INFORMAZIONE ED ELETTRICA E MATEMATICA APPLICATA
EQF7
COMPUTER ENGINEERING
2016/2017

YEAR OF COURSE 2
YEAR OF DIDACTIC SYSTEM 2015
SECONDO SEMESTRE
CFUHOURSACTIVITY
660LESSONS
ANGELO MARCELLI T Curriculum
ANTONIO DELLA CIOPPA Curriculum
Objectives
The course presents the foundations for modelling artificial agents interacting with changing environments. It addresses knowledge representation, problem solving strategies and behavioural learning.

Knowledge and understanding
Methodologies and tools for modelling artificial agents. Understanding the relation among knowledge representation, problem solving strategies and learning.

Applying knowledge and understanding
Mapping methods and tools to complex problems. Design and implementation of artificial agents. Estimation of cost and performance.
Prerequisites
ELEMENTS OF LOGICS, DESIGN OF ALGORITHM AND DATA STRUCTURE
Contents
INTRODUCTION
(LECTURE: 3H)
FUNDAMENTAL CONCEPTS: AGENT, ENVIRONMENT, PERFORMANCE - FOUNDATIONS: THEORY OF COMPUTATION - INTELLIGENT AGENT MODELS
PROBLEM SOLVING
(LECTURE: 15H)
BLIND SEARCH STRATEGIES - INFORMED SEARCH STRATEGIES - LOCAL SEARCH AND OPTIMIZATION PROBLEMS - CSP
ADVERSARIAL SEARCH
(LECTURE: 7H)
GAME THEORY - OPTIMAL DECISION - ALPHA-BETA PRUNING
LOGICAL AGENTS
(LECTURE: 9H)
PROPOSITIONAL LOGIC - THEOREM PROVING - MODEL CHECKING - AGENTS BASED ON PROPOSITIONAL LOGIC
FIRST ORDER LOGIC
(LECTURE: 6H)
SYNTAX AND SEMANTICS - USING FIRST ORDER LOGIC - KNOWLEDGE ENGINEERING AND FIRST ORDER LOGIC
INFERENCE IN FIRST ORDER LOGIC
(LECTURE: 6H)
PROPOSITIONAL VS FIRST ORDER INFERENCE - UNIFICATION AND LIFTING - FORWARD AND BACKWARD CHAINING - RESOLUTION
PROLOG
(LECTURE: 4H; LAB: 10H)
SYNTAX - HORN CLAUSES - UNIFICATION - RECURSION - BACKTRACKING
Teaching Methods
THE COURSE INCLUDES LECTURES AND PRACTICE. DURING PRACTICE, STUDENT TEAMS ARE ASSIGNED A PROJECT THAT INCLUDES INTO A UNITARY FRAMEWORK ALL THE TOPICS OF THE COURSE, AND IS INSTRUMENTAL FOR PROVIDING THE STUDENT WITH THE SKILL FOR APPLYING THE ACQUIRED KNOWLEDGE AND WORKING IN TEAM.
Verification of learning
THE FINAL EVALUATION IS BY ORAL EXAMINATION ON THE CONTENTS OF THE COURSE AND PRESENTATION OF THE PROJECT. THE GRADE IS THE WEIGHTED SUM OF PROJECT CONTENT (70%), PROJECT PRESENTATION (10%) AND ORAL EXAMINATION (20%)
Texts
S. RUSSELL, P. NORVIG, ARTIFICIAL INTELLIGENCE: A MODERN APPROACH, VOLUME I, PEARSON, 3 ED., 2009
L. STERLING, E. SHAPIRO, THE ART OF PROLOG, SECOND EDITION: ADVANCED PROGRAMMING TECHNIQUES, THE MIT PRESS, 1986
More Information
ADDITIONAL MATERIAL IS AVAILABLE ON THE COURSE WEBSITE

The course language is Italian.
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