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Course details
This course provides a basic understanding of the concepts, techniques and general overview of research and development in modern Machine Intelligence. 1. Intelligent agents: agent; structure; environment. 2. Problem solving: Search Strategies, simulated annealing. 3. Game playing: alpha-beta Pruning, game programs. 4. Machine learning: learning from observation, learning by training neural networks, supervised learning, unsupervised learning, learning by simulating evolution - evolutionary algorithms. 5. Pattern recognition: structure of pattern recognition systems, character recognition, image recognition, speech recognition. 6. Robotics: history, classification, architectures, configuration spaces, navigation, motion planning, robotic control. (This course was previously named 'Machine Intelligence B'.)
Course at a glance
| Career: | Undergraduate |
| Credit points: | 6 |
| Requisites: | Prerequisite: COIT 11134 or COIT 11135 |
| Student Contribution Band: | 2 |
| EFTSL: | 0.12500 |
Course availability
| Term | Campus |
|---|---|
| Term 2, 2005 | FLEX ROK |
Course evaluation reports
Course evaluation results may be accessed using the Course Evaluation application in the My.CQU Portal at http://my.cqu.edu.au
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