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DRPS : Course Catalogue : School of Informatics : Informatics

Undergraduate Course: Artificial Intelligence, Present and Future (INFR11180)

Course Outline
SchoolSchool of Informatics CollegeCollege of Science and Engineering
Credit level (Normal year taken)SCQF Level 11 (Year 5 Undergraduate) AvailabilityAvailable to all students
SCQF Credits10 ECTS Credits5
SummaryAI systems now outperform humans on tasks that were once taken to show great intelligence when undertaken by people (for example, playing chess). How far can this go in the future? What are the assumptions behind different approaches to AI? What dangers can there be from AI systems, and how should AI practitioners take these into account? The course gives a quick overview of the background and of contemporary work in symbolic AI, and looks at the relationship between statistical and 2 logical approaches to AI. It also addresses some of the philosophical and ethical issues that arise.
Course description The course surveys the state of the art in current AI, looking at systems and techniques in various subfields (eg, agents and reasoning; planning, constraints and uncertainty; google search and the semantic web; dialogue and machine translation; varieties of learning).

Throughout, relationships between different approaches to AI will be explored, especially the symbolic/sub-symbolic split at the representation level. Philosophical and ethical issues in AI issues will be introduced.

Typical topics include:

Reasoning agents
Logic and inference via Logic Programming
Linked data, semantic net and internet search
Monte Carlo Tree Search
Planning under uncertainty
Adversarial search, game playing
Probabilistic inference
Inductive Logic Programming
Natural language processing, approaches to machine translation
Approaches to machine learning
AI prospects and dangers
Ethical and Philosophical issues.
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Students MUST NOT also be taking Informatics 2D - Reasoning and Agents (INFR08010)
Other requirements None
Information for Visiting Students
Pre-requisitesAs above.
High Demand Course? Yes
Course Delivery Information
Not being delivered
Learning Outcomes
On completion of this course, the student will be able to:
  1. demonstrate knowledge that covers and integrates the current main conceptual frameworks at use in AI
  2. compare and contrast competing approaches towards the construction of AI artefacts
  3. understand and make use of computational reasoning techniques to solve AI problems
  4. clearly present and justify considered opinions on major debates in the field
Reading List
Russell and Norvig: Artificial Intelligence: a Modern Approach, 3rd edition, Prentice Hall, 2016

The Malicious Use of Artificial Intelligence: Forecasting, Prevention, and Mitigation, M. Brundage et al, 2018.
Additional Information
Graduate Attributes and Skills Apply critical analysis, evaluation and synthesis to issues that are informed by forefront developments in the subject/discipline/sector.

Demonstrate and work with a critical understanding of the principal concepts and principles
KeywordsArtificial Intelligence,Reasoning
Course organiserDr Jacques Fleuriot
Tel: (0131 6)50 9342
Course secretaryMs Lindsay Seal
Tel: (0131 6)50 2701
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