Topics /נושאים
Lecturer: Prof. Moshe Sipper
202-1-4791 / 202-1-4741, 2 credits
Course Description
- Students implement software projects in groups of two or three (not one)
- Each group is responsible for all aspects of the project: topic definition, software design, coding, reporting
- Grade is based on final submission
- Final submission is a GitHub repo, with your code and a README file
- The README should include: introduction, method(s), experimental setup, results, conclusions, short usage tutorial
- The project must be submitted by the end of the semester (no extensions except extensive miluim)
The next instance of this course will revolve around evolutionary algorithms using EC-KitY.
🧬 EC-KitY is a scikit-learn-compatible Python tool kit for doing evolutionary computation
🔗 Evolutionary algorithm resources are available here
💡 Ideas for projects:
🧬 EC-KitY is a scikit-learn-compatible Python tool kit for doing evolutionary computation
🔗 Evolutionary algorithm resources are available here
💡 Ideas for projects:
- Implement new algorithms/features: strongly typed GP, coevolution, multiobjective optimization, particle swarm optimization, colony optimization, evolution strategies
- Solve a hard problem using some form of evolutionary algorithm
- Pitch your own idea
Sample reports from previous courses: