Topics in Bio-Inspired Computing (202-1-4791)
Semester B, 2003-2004
Lecturer: Prof. Moshe Sipper
- Projects must be submitted one week after the end of the semester: Friday, June 25, 2004
- No Extensions! (other than miluim/EXTENDED illness)
- You must decide upon a topic until March 24, otherwise 5 points will be taken off
Project Assignment
- + Nir Abraham: maxcut (#2)
- + Idan Gabdank, Ella Mintchikowsky: survivors (#5)
- Elad Levy, Assaf Levy: hp (#4)
- Eran Zakkay: tsp (#1)
- + Noam Weiss: hot spots (# 3)
- + Aviram Iny, Amir Raban: survivors (#5)
- + Alon Klein: evolving CAs (#7)
- + Ben Naidorf, Yoav Fael: evolving questionnaire classifiers using GP
- + Galit Helbron, Ido Kamienietsky: evolving sorting networks (# 6)
- + Dror Banayan, Arik Yelovitch: survivors (#5)
- + Hila Strick: tsp (#1)
Course Description
- Students will work on software projects in the area of evolutionary computation, bio-inspired computing, and artificial life.
Manadatory Reading
General Reference
Administrative Details
Final Report (please read this carefully!)
- The final report must include the following seven sections:
- A short introduction of the domain being investigated.
- A description of the problem or phenomenon studied.
- An explanation of the methods and algorithms employed.
- A description of your programmed system.
- An account of the results obtained.
- Some interesting conclusions.
- Bibliographic references.
- Language: Hebrew or English.
- Length: 10-20 pages.
- Don't include the code.
- Don't send the report by e-mail: hand in a hard copy.
(Evolving) List of Projects:
- Solving the Traveling Salesman Problem (TSP) with genetic algorithms. In this project you'll implement and compare
various GA techniques
to solve instances of TSP from
TSPLIB.
- Solving MAXCUT with genetic algorithms.
In collaboration with Assaf Zaritsky.
- Hot Spots Coevolution.
In collaboration with Assaf Zaritsky.
- Advanced Genetic Algorithm Techniques to Solve the HP Protein Folding Problem.
In collaboration with Ram Janovski.
- Survivors: Struggle for life in a grid world.
In collaboration with Barak Naveh.
- Evolving sorting networks.
- Evolving two-dimensional cellular automata by
cellular programming, and displaying their space-time behavior in 3-D.
-
Gene Expression Programming, a linear-genome version of
Genetic Programming.
- Choose you own project. Note: This option is only open to graduates of the course
Evolutionary Computation and Artificial Life.
Last updated: April 8, 2004.