- Code COMP8420
- Unit Value 6 units
- Offered by Research School of Computer Science
- ANU College ANU College of Engineering and Computer Science
- Course subject Computer Science
- Areas of interest Computer Science, Information Technology
Bio-inspired Computing is the combination of computational intelligence and collective intelligence. These computational methods are used to solve complex problems, and modeled after design principles encountered in natural / biological systems, and tend to be adaptive, reactive, and distributed. The goal of bio-inspired computing is to produce computational tools with enhanced robustness, scalability, flexibility and which can interface more effectively with humans.
- Compare and select the most appropriate method from:
neural, deep learning,
fuzzy, evolutionary or hybrid method for any application /
- Successfully apply that method and analyse the results.
- Demonstrate an advanced theoretical understanding of the differences between these major bio-inspired computing methods, including the advantages and disadvantages of each
- Neural networks/Deep learning assignment 15%
- Neural networks/Deep learning/Fuzzy midterm quiz 15%
- Evolutionary/hybrid assignment 15%
- Active participation 5%
- Final Exam 50%
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WorkloadThirty hours of lectures and six two-hour tutorial/laboratory sessions
Requisite and Incompatibility
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- Student Contribution Band:
- Band 2
- Unit value:
- 6 units
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Offerings and Dates
|Class number||Class start date||Last day to enrol||Census date||Class end date||Mode Of Delivery|
|4043||19 Feb 2018||26 Feb 2018||31 Mar 2018||25 May 2018||In Person|