COMP24011
Introduction to AI
10
Semester 1
Undergraduate
Level 2
Ian Pratt-Hartmann
Unit coordinator
Department of Computer Science
1
FHEQ level (Framework for Higher Education Qualifications) ' Middle part of Bachelors '
European Credit Transfer & Accumulation System Rating : 5.0
<p>The Unit constitutes an introduction to the field of Artificial Intelligence, aiming at once to give a broad overview of the subject and to serve as a basis for more detailed third year courses, particularly, COMP34111 (AI and Games), COMP34212 (Cognitive Robotics), COMP34812 (Natural Language Understanding) and COMP37212 (Computer Vision).</p>
<p>The Unit constitutes an introduction to the field of Artificial Intelligence, aiming at once to give a broad overview of the subject and to serve as a basis for more detailed third year courses, particularly, COMP34111 (AI and Games), COMP34212 (Cognitive Robotics), COMP34812 (Natural Language Understanding) and COMP37212 (Computer Vision).</p>
<p><span style="background-color:rgb(255,255,255);"><span class="EOP SCXW9819729 BCX0" style="-webkit-tap-highlight-color:transparent;-webkit-text-stroke-width:0px;-webkit-user-drag:none;font-family:Aptos, Aptos_EmbeddedFont, Aptos_MSFontService, sans-serif;font-size:11pt;font-style:normal;font-variant-caps:normal;font-variant-ligatures:normal;font-weight:400;letter-spacing:normal;line-height:18.3458px;margin:0px;orphans:2;padding:0px;text-align:left;text-decoration-color:initial;text-decoration-style:initial;text-decoration-thickness:initial;text-indent:0px;text-transform:none;user-select:text;white-space:normal;widows:2;word-spacing:0px;" data-ccp-props="{"335559738":60,"335559739":60}">A student completing this course should: be able to implement basic search- and planning-algorithms from Artificial Intelligence, and apply them to real-world problems; be able to apply first-order logic to model physical situations and reason about the effects of actions, to appreciate the limitations of logic and to select appropriate responses to these limitations; be able to develop formal ontologies to represent knowledge in different domains; be able to select and apply the principal models of uncertainty employed in Artificial Intelligence in concrete problem-solving situations; be able to solve the problem of sensor integration, and to implement simultaneous localization and mapping in robotics; be able to apply techniques for representing (qualitative) temporal and spatial information in Artificial Intelligence; have an appreciation of the central philosophical problems connected with artificial intelligence. </span></span></p>
<p><strong>ILO 1: </strong>apply language models and information extraction techniques to solve problems in AI.</p><p><strong>ILO 2:</strong> apply first-order logic to model physical situations and to reason about the effects of actions.</p><p><strong>ILO 3: </strong>develop formal ontologies to represent knowledge in different domains.</p><p><strong>ILO 4:</strong> implement basic search- and planning-algorithms from Artificial Intelligence, and apply them to real-world problems.</p><p><strong>ILO 5:</strong> solve the problem of sensor integration, and to implement simultaneous localization and mapping in robotics.</p><p><strong>ILO 6: </strong>select and apply the principal models of uncertainty employed in Artificial Intelligence in concrete problem-solving situations</p>
<div> Topic 1. Search and planning:</div><div> problem-solving as search; adversarial games; classical planning.</div><div> Topic 2. Logic and reasoning</div><div> review of first-order logic; applications of logic to planning; logic versus reasoning; default `logic'.</div><div> Topic 3. AI and probability</div><div> review of probability theory; alternative representations of uncertainly; Bayes' networks.</div><div> Topic 4. Knowledge representation</div><div> ontology-driven database access; formal ontologies and knowledge-representation.</div><div> Topic 5. The periphery:</div><div> sensors and actuators; sensor integration, simultaneous localization and mapping.</div><div> Topic 6. Philosophical issues:</div><div> the Turing test; the meaning of `AI'; the problem of consciousness.</div>
<p>2 hours lectures per week (22 hours in total), 2 hours of lab per fortnight (8 hours in total)</p>
1
Written exam
80%
2
Written assignment (inc essay)
20%
<p>Exam and assessments</p><div>Coursework:</div><div> </div><div>Lab 1: Games</div><div>Lab 2: Constraints </div><div>Lab 3: SLAM </div><div>Lab 4: BM25</div>
COMP11120
Mathematical Techniques for Computer Science
Pre-Requisite
Compulsory
COMP13212
Data Science
Pre-Requisite
Compulsory
MATH11121
Mathematical Foundations & Analysis
Pre-Requisite
Compulsory
COMP11120 (for CS students) and MATH11121 or equivalent (for CM students). COMP13212 is a pre-requisite for all.<p>COMP11120 (for CS students) and MATH11121 or equivalent (for CM students). COMP13212 is a pre-requisite for all.</p>
Y
<ol><li>Russell, Stuart J. (2022). <i>Artificial intelligence: a modern approach</i>. Pearson. ISBN:<a href="https://www.librarysearch.manchester.ac.uk/discovery/search?query=isbn,contains,9781292401133&search_scope=MyInst_and_CI&sortby=rank&vid=44MAN_INST:MU_NUI&lang=en&mode=advanced&offset=0" target="_blank"> 9781292401133</a><br> </li><li>Prince, Simon J. D. (2012). <i>Computer vision: models, learning, and inference</i>. Cambridge University Press. ISBN:<a href="https://www.librarysearch.manchester.ac.uk/discovery/search?query=isbn,contains,1107011795&search_scope=MyInst_and_CI&sortby=rank&vid=44MAN_INST:MU_NUI&lang=en&mode=advanced&offset=0" target="_blank"> 1107011795</a><br> </li><li>Szeliski, Richard. (2022). <i>Computer vision: algorithms and applications</i>. Springer. ISBN:<a href="https://www.librarysearch.manchester.ac.uk/discovery/search?query=isbn,contains,9783030343729&search_scope=MyInst_and_CI&sortby=rank&vid=44MAN_INST:MU_NUI&lang=en&mode=advanced&offset=0" target="_blank"> 9783030343729</a><br> </li><li>Ben-Ari, Mordechai. <i>Mathematical Logic for Computer Science</i>. Springer London. ISBN:<a href="https://www.librarysearch.manchester.ac.uk/discovery/search?query=isbn,contains,1447141288&search_scope=MyInst_and_CI&sortby=rank&vid=44MAN_INST:MU_NUI&lang=en&mode=advanced&offset=0" target="_blank"> 1447141288 </a></li></ol>
Lectures
22
Practical classes & workshops
8
0
70