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CODE ICS1017

 
TITLE Foundations of Artificial Intelligence

 
LEVEL 01 - Year 1 in Modular Undergraduate Course

 
ECTS CREDITS 4

 
DEPARTMENT Artificial Intelligence

 
DESCRIPTION Artificial intelligence has been described as the study of how to get machines to do the things that humans do best. This study-unit introduces fundamental concepts in Artificial Intelligence from a theoretical, practical and cognitive point of view. It raises questions about what "intelligence" is and whether machines can have intelligent properties.

There are four major schools of thought about what AI is: 1) AI systems that think like humans; 2) AI systems that act like humans; 3) AI systems that think rationally; and, 4) AI systems that act rationally.

AI research and development is active in each area, but each area has different ideas about whether AI will be successful because systems are intelligent in the same way that humans are intelligent or whether systems can be considered intelligent because a human is satisfied that, regardless of how the system solved the problem, the result is the same that a human would have produced.

Students will be introduced to typical problems that AI systems try to solve, including Perceiving the environment; Learning, and learning how to learn; Communicating with humans; Acquiring knowledge, including general knowledge; Representing knowledge; Reasoning with information and knowledge; Autonomous Agents; Decision Making; Interacting with the environment; and Artificial Intelligence and Cognitive Science.

Study-unit Aims:

The aims of this study-unit are to:
- Introduce students to the rationale for AI approaches to problem solving by covering situated AI techniques such as: problem solving as search; state spaces; searching in graphs; heuristic searches; First order logic (FOL); Planning; Universes of discourse; Propositional calculus; Reasoning by abduction (vs deduction and induction); Reasoning under uncertainty; Supervised and unsupervised learning techniques;
- Expose students to how artificial intelligence relates to the broader scope of cognitive science by considering how AI can contribute to understanding natural intelligence and how the sciences of mind (e.g. neuroscience, psychology, philosophy, linguistics) can inform approaches to the design and construction of artificial intelligence.

Learning Outcomes:

1. Knowledge & Understanding:

By the end of the study-unit the student will be able to:
- Explain in simple terms what kinds of problems are considered AI problem;
- Explain why there are different approaches problem-solving in AI;
- Identify which AI techniques are appropriate for solving various typical AI problems;
- Distinguish between different AI techniques to solve the same AI problem.

2. Skills:

By the end of the study-unit the student will be able to:
- Use any of the AI techniques covered to solve simple problems;
- Compare the appropriateness of a number of AI techniques to solve simple problems;
- Represent facts and knowledge using different knowledge representation schemes.

Main Text/s and any supplementary readings:

- Poole, D. and Mackworth, A. (2010). “Artificial Intelligence: Foundations of Computational Agents”. Cambridge University Press. Available on-line at http://artint.info/html/ArtInt.html.
- Russel, S. and Norvig, P. (2009). “Artificial Intelligence: A Modern Approach”. Prentice Hall. 3rd Edition.

 
STUDY-UNIT TYPE Lecture and Independent Study

 
METHOD OF ASSESSMENT
Assessment Component/s Resit Availability Weighting
Examination (2 Hours) Yes 100%

 
LECTURER/S Charles Abela
Joel Azzopardi
Claudia Borg
Vanessa Camilleri
Alexiei Dingli
Kristian Guillaumier
Christopher D. Staff (Co-ord.)

 
The University makes every effort to ensure that the published Courses Plans, Programmes of Study and Study-Unit information are complete and up-to-date at the time of publication. The University reserves the right to make changes in case errors are detected after publication.
The availability of optional units may be subject to timetabling constraints.
Units not attracting a sufficient number of registrations may be withdrawn without notice.
It should be noted that all the information in the study-unit description above applies to the academic year 2017/8, if study-unit is available during this academic year, and may be subject to change in subsequent years.
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