Software Project Possibilities: The best projects are those which can be converted into a science fair project. Extra credit will be granted if this is done. Possible ideas are as follows:

  1. Artificial Intelligence: This attempt to simulate the human brain functions. This includes neural networks which are computer programs which learn.
  2. Artificial Life: Uses computer simulations to derive general theories about life. the Scientific American article "ARTIFICIAL LIFE: Boids of a Feather Flock Together" is a great place to start.
  3. Cellular automata: Cellular automata are computer programs that try to simulate life at the cellular level. They attempt to explain how undifferentiated cells can divide and become complex structures such as appendages.
  4. Chaos Theory: This deals with non linear systems which can become chaotic. It includes various forms of turbulence, animal populations, climate and the stock market.
  5. Fractals: These use relatively simple iterated equations to produce elaborate graphics.
  6. Number Series: There are many different type. Computers are commonly used to discover new members of various series. This includes the search for perfect numbers, mersenne primes, etc.
  7. Spam Filters: These devices are used for blocking e-mail spam. They can range from very sophisticated to very simple filters and can be fairly simple to write.
  8. Markov Chains:
  9. Physics Simulations Accounting for Air Resistance: The reason air resistance is ignored in most calculations has to do with the fact that it generally requires a computer to do account for it.
  10. Random Number Generators: There's no such thing as a perfect random number generator. Usually they have to strike a balance between performance and speed and are still a topic of research among computer scientists.
  11. Monte Carlo Simulations: These are programs which use random number generators to simulate complex problems. They can be extremely complex or very simple. Simple simulations of this type can be done with relatively little programming experience. The Marine Biology case study is an example of a Monte Carlo Simulation.
  12. Flocking/herding Behavior: Programs of this type attempt to simulate the behavior of predators and prey using simple sets of rules.
  13. Snow Flake/Crystal Growth: Look at thousands of pictures of snow flakes and they all tend to be slightly different yet they are recognizable as snow flakes. This implies that there are simple rules which can govern how the crystals are formed.