**Semester B, 2001-2002**

**Lecturer: Prof. Moshe Sipper**

- Searching for Solutions to the Traveling Salesman Problem (TSP) using an
Algorithm Simulating a Nest of Ants.

Source: Dorigo M., V. Maniezzo & A. Colorni (1996). The Ant System: Optimization by a Colony of Cooperating Agents.*IEEE Transactions on Systems, Man, and Cybernetics-Part B*, 26(1):29-41. - Genetic Art: Creating Computer Images via Evolution.

Source: K. Sims, Artificial Evolution for Computer Graphics,*Computer Graphics*, Vol. 25, No. 4, July 1991, pp. 319-328. - Co-Evolving Non-Uniform Cellular Automata to Perform Computations.

Source: M. Sipper, Co-Evolving Non-Uniform Cellular Automata to Perform Computations, Physica D, vol. 92, pp. 193-208, 1996. - Cooperative Coevolution.

Source: M. A. Potter and K. A. De Jong, Cooperative Coevolution: An Architecture for Evolving Coadapted Subcomponents,*Evolutionary Computation*, Vol. 8, No. 1, Spring 2000. - Self-Replicating Loops.

Source: H. Sayama A New Structurally Dissolvable Self-Reproducing Loop Evolving in a Simple Cellular Automata Space,*Artificial Life*, Vol. 5, No. 4, Fall 1999.

More information can be found here. - Using Self-Replicating Loops to Solve the (NP-Complete) Problem of
Satisfiability.

Source: H.-H. Chou and J. A. Reggia, Problem Solving During Artificial Selection of Self-Replicating Loops,*Physica D*, Vol. 115, No. 3-4, 1998, pp. 293-312. The abstract is available here, and the article itself can be photocopied at the central library.

Also read the following article about the Trend environment. - A Simulator for Braitenberg Vehicles (a series of simulated robots, going from
very simple ones to more complex ones).

Source: V. Braitenberg,*Vehicles: Experiments in Synthetic Psychology*, The MIT Press, 1984, Cambridge, Massachusetts. (A small, beautifully written book.) - Select a hard problem you've encountered during your computer-science
studies, and attempt to solve it with a genetic algorithm.

Source: M. Tomassini, Evolutionary Algorithms. - A Java Applet Demonstrating the Workings of a Genetic Algorithm (must work in browser mode).

Source: M. Tomassini, Evolutionary Algorithms.

- Course reference: 202-1-4791.
- Web: www.cs.bgu.ac.il/~sipper/courses/topics02b/.
- Prerequisite: The course is intended for third-year students.
- Credits: 2.
- Time: Monday 10-12.
- Place: Building 34, Room 9.
- Grade:
- 70%: Project evaluation.
- 30%: Final report.

- Students may work on their own or in pairs.
- The final report (between 10-20 pages) should include the following 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;
- (hopefully...) some interesting conclusions;
- bibliographic references.