COMP08035 2018 Artificial Intelligence
Full Title
Artificial Intelligence
Transcript Title
Artificial Intelligence
Code
COMP08035
Attendance
70 %
Subject Area
COMP - 0613 Computer Science
Department
COMP - Computing & Creative Practices
Level
08 - Level 8
Credit
05 - 05 Credits
Duration
Semester
Fee
€
Start Term
2018 - Full Academic Year 2018-19
End Term
9999 - The End of Time
Author(s)
John Weir, Donny Hurley, Paul Powell
Programme Membership
SG_KSMAR_H08 201800 Bachelor of Science (Honours) in Computing in Smart Technologies
SG_KSODV_H08 201800 Bachelor of Science (Honours) in Computing in Software Development
SG_KCMPU_H08 201800 Bachelor of Science (Honours) in Computing
SG_KSODV_K08 201800 Level 8 Honours Degree Add-on in Software Development
SG_KSFTD_K08 201800 Bachelor of Science (Honours) in Computing in Software Development (Add On)
SG_ETRON_K08 201900 Bachelor of Engineering (Honours) in Electronic and Computer Engineering
SG_KSFTD_K08 201900 Bachelor of Science (Honours) in Computing in Software Development (Add On)
SG_KSODV_K08 201900 Level 8 Honours Degree Add-on in Software Development
SG_KSMAR_H08 201900 Bachelor of Science (Honours) in Computing in Smart Technologies
SG_KSODV_H08 201900 Bachelor of Science (Honours) in Computing in Software Development
SG_KCMPU_H08 201900 Bachelor of Science (Honours) in Computing
SG_KCMPU_H08 202000 Bachelor of Science (Honours) in Computing
SG_KSODV_H08 202000 Bachelor of Science (Honours) in Computing in Software Development
SG_KSFTD_K08 202000 Bachelor of Science (Honours) in Computing in Software Development (Add On)
SG_KSODV_K08 202000 Level 8 Honours Degree Add-on in Software Development
SG_EELCO_K08 202000 Bachelor of Engineering (Honours) in Electronic and Computer Engineering
SG_KSMAR_H08 202000 Bachelor of Science (Honours) in Computing in Smart Technologies
SG_KSODV_H08 202100 Bachelor of Science (Honours) in Computing in Software Development
SG_KCMPU_H08 202100 Bachelor of Science (Honours) in Computing
SG_KSMAR_H08 202100 Bachelor of Science (Honours) in Computing in Smart Technologies
SG_KSODV_H08 202200 Bachelor of Science (Honours) in Computing in Software Development
SG_KSFTD_K08 202200 Bachelor of Science (Honours) in Computing in Software Development (Add-on)
SG_KSODV_K08 202200 Bachelor of Science (Honours) in Computing in Software Development (Add-on)
SG_KCMPU_H08 202200 Bachelor of Science (Honours) in Computing
SG_KSODV_H08 202400 Bachelor of Science (Honours) in Computing in Software Development
SG_KSODV_K08 202400 Bachelor of Science (Honours) in Computing in Software Development
SG_KSFTD_K08 202400 Bachelor of Science (Honours) in Computing in Software Development
SG_KCMPU_H08 202400 Bachelor of Science (Honours) in Computing
SG_KCMPT_K08 202400 Bachelor of Science (Honours) in Computing
Description
This subject aims to make students aware of the many areas of artificial intelligence and the tools available for AI type solutions. Identify suitable problems for AI solutions. Examine in detail and implement structures for representing knowledge. The manipulation of knowledge, especially rule based systems. Implementing some of the AI techniques that have been introduced with AI Programming Languages.
Learning Outcomes
On completion of this module the learner will/should be able to;
1.
Demonstrate Knowledge in the foundation and general principles of Artificial Intelligence
2.
Identify the types of AI solutions that can be formulated
3.
Apply represenations to problem domains
4.
Recognise structure and program various knowledge representations
Teaching and Learning Strategies
A mixture of theoretical and practical delivery.
Module Assessment Strategies
Students will apply sample code to problems to demonstrate theoretical concepts introduced culminating in an assessment to apply techniques to a Logical representation, search and exploration problem.
Demonstrate the usage data structures such as Lists in a logic based approach.
Use provided search code and adjust it to a new representation.
Write a logic based meta-interpreter program to enable a computer to provide a solution while explaining the proof for a given problem to be solved.
Repeat Assessments
Repeat exam
Indicative Syllabus
Demonstrate Knowledge in the foundation and general principles of Artificial Intelligence
Be Aware of the types of AI solutions that can be formulated
Apply represenations to problem domains
Recognise structure and program various knowledge representations
Demonstrate Knowledge in the foundation and general principles of Artificial Intelligence
Examine Logical Intelligent Agents
Mapping real world logic onto computational logic models using First order logic
Formulation of FOL statements
FOL Proofs
Be Aware of the types of AI solutions that can be formulated
Fol based Rules
Semantic networks
Neural Networks
Rule based systems
Game and search trees.
Apply represenations to problem domains
Represent problem and search spaces.
Heuristic representation
Represent and program search methods as a means of manipulating search spaces.
Machine Learning
Structure and flavours of Meta-level interpreters
Rule structure and interpretation
Rule independence and control of inference
Explanation facility
Expert system structure
Recognise structure and program various knowledge representations
Data structures in procedural language for rich representation
Predicate based programming
Functional based programming
List representation and manipulation
Apply Heuristic search methods
Search State and Game representation and manipulation
Coursework & Assessment Breakdown
Coursework & Continuous Assessment
30 %
End of Semester / Year Formal Exam
70 %
Coursework Assessment
| Title | Type | Form | Percent | Week | Learning Outcomes Assessed | |
|---|---|---|---|---|---|---|
| 1 | Continuous Assessment Various procedural, logical and functional programming tasks covering the theoretical aspects of the course | Coursework Assessment | Assessment | 30 % | Week 13 | 2,3,4 |
End of Semester / Year Assessment
| Title | Type | Form | Percent | Week | Learning Outcomes Assessed | |
|---|---|---|---|---|---|---|
| 1 | Final Exam | Final Exam | Closed Book Exam | 70 % | Week 15 | 1,2,3,4 |
Full Time Mode Workload
| Type | Location | Description | Hours | Frequency | Avg Workload |
|---|---|---|---|---|---|
| Practical / Laboratory | Computer Laboratory | Coding AI techniques | 2 | Weekly | 2.00 |
| Lecture | Lecture Theatre | Theory | 2 | Weekly | 2.00 |
| Independent Learning | Not Specified | Independent Learning | 3 | Weekly | 3.00 |
Total Full Time Average Weekly Learner Contact Time 4.00 Hours
Online Learning Mode Workload
| Type | Location | Description | Hours | Frequency | Avg Workload |
|---|---|---|---|---|---|
| Lecture | Online | Online Delivery | 2.3 | Weekly | 2.30 |
| Directed Learning | Not Specified | Directed Learning | 1.12 | Weekly | 1.12 |
| Independent Learning | Not Specified | Independent Learning | 3.5 | Weekly | 3.50 |
Total Online Learning Average Weekly Learner Contact Time 2.30 Hours
Required & Recommended Book List
Recommended Reading
2015 Artificial Intelligence : A Modern Approach, 3Rd Edition PE
ISBN 9332543518 ISBN-13 9789332543515
2015 Artificial Intelligence : A Modern Approach, 3Rd Edition PE
ISBN 9332543518 ISBN-13 9789332543515
Brand New
Recommended Reading
2009-12-01 Artificial Intelligence: A Modern Approach (Prentice Hall Series in Artificial Intelligence) Pearson
ISBN 0136042597 ISBN-13 9780136042594
2009-12-01 Artificial Intelligence: A Modern Approach (Prentice Hall Series in Artificial Intelligence) Pearson
ISBN 0136042597 ISBN-13 9780136042594
Artificial Intelligence: A Modern Approach 3e" offers the most comprehensive up-to-date introduction to the theory and practice of artificial intelligence. Number one in its field this textbook is ideal for one or two-semester undergraduate or graduate-level courses in Artificial Intelligence.Dr. Peter Norvig contributing "Artificial Intelligence "author and Professor Sebastian Thrun a Pearson author are offering a free online course at Stanford University on artificial intelligence. According to an article in "The New York Times the course on artificial intelligence is one of three being offered experimentally by the Stanford computer science department to extend technology knowledge and skills beyond this elite campus to the entire world." One of the other two courses
Recommended Reading
2017-09-25 Artificial Intelligence: Foundations of Computational Agents Cambridge University Press
ISBN 110719539X ISBN-13 9781107195394
2017-09-25 Artificial Intelligence: Foundations of Computational Agents Cambridge University Press
ISBN 110719539X ISBN-13 9781107195394
Recommended Reading
2011-08-24 Prolog Programming for Artificial Intelligence (International Computer Science Series) Addison Wesley
ISBN 0321417461 ISBN-13 9780321417466
2011-08-24 Prolog Programming for Artificial Intelligence (International Computer Science Series) Addison Wesley
ISBN 0321417461 ISBN-13 9780321417466
PROLOG Programming for Artificial Intelligence The fourth edition of this best-selling guide to Prolog and Artificial Intelligence has been updated to include key developments in the field while retaining its lucid approach to these topics. New and extended topics include Constraint Logic Programming, abductive reasoning and partial order planning. Divided into two parts, the first part of the book introduces the programming language Prolog, ... Full description
Module Resources
Journal Resources
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URL Resources
Moodle Course Notes.
Other Resources
None
Additional Information
None