COMP30490 Collective Intelligence

Academic Year 2016/2017

To many the promise of artificial intelligence (AI) -- the creation of a computational intelligence to rival our own -- represents the holy grail of computer science and almost every computer science curriculum will include modules to cover the state-of-the-art in AI tools and techniques. However recently there has been a subtle but important shift in the way that humans and machines can combine their efforts to solve challenging problems. Instead of developing stand-alone AI algorithms capable of complex problem solving, planning, learning, and even perception, researchers and engineers have recognised the power of the Web as a platform for so-called collective intelligence, where humans and machines can combine their different skills to solve problems that are otherwise beyond the research of modern AI. This course will explore this new science of collective intelligence, providing concrete examples of how some of the most complex problems (e.g., understanding images, reading text, translating speech, recognising relevant information, answering questions, even predicting future events etc) can be successfully solved by harnessing the collective intelligence of the Web. The course will also consider how the business of the Web has adapted to take advantage of collective intelligence with special attention paid to some of the emerging business models that have developed as a result. This course will include substantial coursework and a Java-based programming project. Please note that proficiency in the Java Programming Language is required.

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Curricular information is subject to change

Learning Outcomes:

- Understanding the underlying principles of collective intelligence.
- Understanding key algorithms and approaches (e.g. games with a purpose, collaborative filtering, social filtering, particpatory sensing, etc.)
- How to develop your own collective intelligence solution as part of a major practical project.
- Understanding how the business of the Web is harnessing collective intelligence.

Student Effort Hours: 
Student Effort Type Hours
Lectures

24

Practical

50

Laboratories

20

Total

94

 
Requirements, Exclusions and Recommendations
Learning Requirements:

Proficiency in the Java (or Python) Programming Language is required. Students must be able to programme using modern data structures and techniques.



 
Description % of Final Grade Timing
Project: GWAP Project

50

Throughout the Trimester
Project: Collective Intelligence Mini Project

50

Throughout the Trimester

Compensation

This module is not passable by compensation

Resit Opportunities

In-semester assessment

Remediation

If you fail this module you may retake it.

Name Role
Mr Khalil Muhammad Tutor