DS 7778: Nature-Inspired Computing

This is a proposed special-topics course (Not yet approved!)

Prerequisites: DS3500 or CS3500
When: Jan 9th to Apr 19th. Meeting times to be announced.
Where: Online on Zoom

Instructor

John Rachlin
Assistant Teaching Professor
Email: j.rachlin@northeastern.edu
Office Hours: TBD

Course Description

This is a survey course in computational techniques inspired by nature and their use in data-driven problem-solving. Topics will include genetic algorithms and evolutionary computing, ant colony and particle swarm optimization, artificial immune systems, neural computing, simulated annealing, and cellular automata for modeling and simulating complex systems. Students will read and review both seminal and current research papers, implement methods and algorithms in Python or Java, and investigate how well these techniques work for a variety of problem domains including manufacturing, resource allocation, constraint-satisfaction problems, bioinformatics, and classification. The course will also include a final class project that students will present in an end-of-semester conference-style poster session. The course requires a solid understanding of at least one high-level programming language. Prerequisites: DS3500 or CS3500.

Readings

There will be about one research paper or chapter assigned each week including the following:

Rout M., Rout J., and Das H., eds. (2020). Nature Inspired Computing for Data Science, Studies in Computational Intelligence (871), Springer Switzerland AG.

Ibrahim D. (2016). An overview of soft computing. 12th International Conference on Application of Fuzzy Systems and Soft Computing, ICAFS 2016, 29-30 August 2016, Vienna, Austria

Siddique N. and Adeli H. (2015). Nature Inspired Computing: An Overview and Some Future Directions. Cogn Comput 7:706–714

Kari L. and Rozenberg G. (2008). The many facets of Natural Computing, Communications of the ACM, Vol 51, No 10.

Dorigo M., Maniezzo V., and Colorni A. (1996). Ant System: Optimization by a Colony of Cooperating Agents, IEEE Transactions on Systems, Man, and Cybernetics, Vol 26, No 1.

Homework

Assigned weekly or every other week depending on the assignment complexity. Students are expected to code their own solutions. Collaborating beyond verbal discussions of the problems is not allowed.

Class Project

The class project is an opportunity to explore the world of scientific computing in an area of your own choosing. At the end of the semester, students will present their results in a conference-style poster session and projects will be collected into the conference Proceedings.

Academic Integrity

Computer Science is a creative process. Individuals must reach their own understanding of problems and discover paths to their solutions. During this time, discussions with friends and colleagues are encouraged—you will do much better in the course, and at Northeastern, if you find people with whom you regularly discuss problems. But those discussions should take place verbally. Each programming submission must be entirely your own work. The university's academic integrity policy discusses actions regarded as violations and consequences for students: http://www.northeastern.edu/osccr/academic-integrity

Questions?

As noted above, this is a proposed course (not yet approved.) If you would be interested in taking this course or would like to discuss possible topics in Nature-Inspired Computing, please contact Prof. Rachlin

Evaluation

The final grade for this course will be weighted as follows:

• Homework 75%
• Class Project: 25%

Final grades will be rounded to the nearest integer and assigned based on the following scale (e.g., 92.4999 is a 92 whereas 92.5000 is a 93.):

Letter	Range
A	95 - 100
A-	90 - 92
B+	87 - 89
B	83 - 86
B-	80 - 82
C+	77 - 79
C	73 - 76
C-	70 - 72
D+	67 - 69
D	63 - 66
D-	60 - 62
F	<60