Module Details |
The information contained in this module specification was correct at the time of publication but may be subject to change, either during the session because of unforeseen circumstances, or following review of the module at the end of the session. Queries about the module should be directed to the member of staff with responsibility for the module. |
Title | Reasoning and Intelligent Systems | ||
Code | CKOL502 | ||
Coordinator |
Dr F Grasso Computer Science Floriana@liverpool.ac.uk |
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Year | CATS Level | Semester | CATS Value |
Session 2019-20 | Level 7 FHEQ | Whole Session | 15 |
Aims |
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1. To provide students with a comprehensive understanding of the domain of reasoning and intelligent systems. 2. To enable students to evaluate modern techniques of artificial intelligence and reasoning in both the public and the private sector contexts. 3. To provide students with the knowledge and skills required to develop and deploy the tools and techniques of intelligent systems to solve real world problems. |
Learning Outcomes |
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(M1) An ability to analyse and evaluate intelligent systems techniques. |
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(M2) A comprehensive understanding of the differences between intelligent system applications and conventional computer applications. |
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(M3) An ability to deploy critically appropriate software tools and skills for the design and implementation of intelligent systems. |
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(M4) An in depth understanding of the practical application of the principles of intelligent systems. |
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(M5) An ability to analyse intelligent system problems and formulate appropriate solutions. |
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(S1) Communication skills in electronic as well as written form. |
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(S2) Self-direction and originality in tackling and solving problems within the domain of Computer Science, and an ability to act autonomously in planning and implementing solutions in a professional manner. |
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(S3) Experience of working in development teams and the leadership of such teams. |
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(S4) Group working, respecting others, co-operating, negotiating/persuading, awareness of interdependence with others. |
Syllabus |
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Week 1: Introduction to Intelligent systems Week 2: Rule-based Expert Systems Week 3: Reasoning under uncertainty Week 4: Evolutionary Computation Algorithms Week 5: Fuzzy Expert Systems Week 6: Inductive reasoning Week 7: Temporal and spatial reasoning Week 8: Intelligent systems applications |
Teaching and Learning Strategies |
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The mode of delivery is by online learning, facilitated by a Virtual Learning Environment (VLE). This mode of study enables students to pursue modules via home study while continuing in employment. Module delivery involves the establishment of a virtual classroom in which a relatively small group of students (usually 10-25) work under the direction of a faculty member. Module delivery proceeds via a series of eight one-week online sessions, each of which comprises an online lecture, supported by other eLearning activities, posted electronically to a public folder in the virtual classroom. The eLearning activities will include lecture casts, live seminar sessions, self-assessment activities, reading materials and other multimedia resources. Communication within the virtual classroom is asynchronous, preserving the requirement that students are able to pursue the course in their own time, within the weekly time-frame of each seminar. An important element of the module provision is act ive learning through collaborative, cohort-based, learning using discussion fora where the students engage in assessed discussions facilitated by the faculty member responsible for the module. This in turn encourages both confidence and global citizenship (given the international nature of the online student body). |
Teaching Schedule |
Lectures | Seminars | Tutorials | Lab Practicals | Fieldwork Placement | Other | TOTAL | |
Study Hours |
24 |
40 |
64 | ||||
Timetable (if known) | |||||||
Private Study | 86 | ||||||
TOTAL HOURS | 150 |
Assessment |
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EXAM | Duration | Timing (Semester) |
% of final mark |
Resit/resubmission opportunity |
Penalty for late submission |
Notes |
CONTINUOUS | Duration | Timing (Semester) |
% of final mark |
Resit/resubmission opportunity |
Penalty for late submission |
Notes |
Report: Intelligent systems group project resulting in a demonstrable system and a group report describing and analysing the system. | 2000-2500 words | 30 | ||||
Programming: Individual software solution to an intelligent systems' problem resulting in a demonstrable software system and supporting analysis in the form of a brief report (500 words). | 12 hours | 30 | ||||
Discussion Question 1: Participate actively in an online discussion to critically discuss experiences and opinions within the cohort relating to intelligent systems. | 1000-1500 words | 20 | ||||
Discussion Question 2: Participate actively in an online discussion concerning one of the intelligent systems topics covered within the module, demonstrating an understanding of the key issues and sho | 1000-1500 words | 20 |
Recommended Texts |
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Reading lists are managed at readinglists.liverpool.ac.uk. Click here to access the reading lists for this module. |