COMP6380

Machine Intelligence

10 Units

This course provides an overview about important past and current developments, concepts, and applications in the fast evolving field of machine intelligence. It is an introductory course and could later be extended by higher studies in areas such as, advanced machine learning, data mining, bioinformatics, deep learning, optimisation, autonomous agents, computer vision, computer graphics, and related fields. The course’s topic is a central part of computer science and software engineering. Many of the concepts addressed by this course were initially biologically motivated and fall under the umbrella of brain theory. The aim is to get an understanding of intelligence, learning, memory, language, and the workings of the human brain by modelling and implementing aspects of these concepts in the computer. With the availability of faster workstations and sophisticated robotic hardware, machine intelligence methods can find more widespread applications. This course will address applications and systems where machine intelligence methods can lead to significant advancements, often surprising solutions, and sometimes triumphal success.

Faculty Faculty of Engineering and Built Environment
School School of Electrical Engineering and Computing
Availability

Not currently offered

Learning Outcomes

On successful completion of this course, students will be able to:

  1. apply Artificial Intelligence (AI) techniques;
  2. demonstrate their understanding and apply examples of machine learning methods.
  3. explain past and current developments in machine intelligence.
  4. demonstrate the ability to project towards future developments of the field including possible ethical implications in areas such as data mining and robotics.as data mining and robotics.
Content
  1. Neural Networks and Brain Mechanisms

  2. Machine Learning

  3. Adaptive Robotics

  4. Search and Prediction in Games

  5. Evolutionary Algorithms

  6. Automated Reasoning and Logic

Requisites
  • This course has similarities to COMP3330. If you have successfully completed COMP3330 you cannot enrol in this course.
Assumed Knowledge Equivalent to a completed 2nd year Bachelor of Computer Science
Assessment Items
  • Presentation: History and Philosophy Assignment
  • Written Assignment: Homework Assignment 1
  • In Term Test: Mid Term Test
  • Written Assignment: Homework Assignment 2
  • Formal Examination: Formal Examination *

* This assessment has a compulsory requirement.

Contact Hours

Callaghan

Computer Lab

Face to Face On Campus 2 hour(s) per Week for Full Term
- None. But it is highly recommended to attend all lectures and labs.

Lecture

Face to Face On Campus 2 hour(s) per Week for Full Term

Compulsory Requirements
  • Course Assessment Requirements: 1. Formal Examination: Minimum Grade / Mark Requirement - Students must obtain a specified minimum grade / mark in this assessment item to pass the course. (Assessment 5 - Formal Examination: Minimum Grade / Mark Requirement - Students must obtain a specified minimum grade / mark in this assessment item to pass the course. Students must obtain 40% in the final exam to pass the course.)
Timetable 2017 Course Timetables for COMP6380
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