AiS Challenge Team Interim

Team Number: 051

School Name: Manzano High School

Area of Science: Science

Project Title: Predator and Prey Models

 

 


Our group has learned many important skills required for success in the Adventures in Supercomputing Challenge. Ever since the first day of class, our instructor has been teaching us the necessary aspects that are required in the curriculum.

First, we spent six weeks learning the general aspects of html. We learned about hyper links, placing images on a web page, placing colors, and cutting and pasting. Our final project in that rubric was to create our very own web page consisting of pictures, html codes, and placing tables. We edited an existing web page by replacing it with our own files and folders.

Then, we spent two to three weeks setting up both MHS AiS Challenge Linux accounts and accessing our New Mexico AiS Challenge Unix accounts. In our local Linux domain, we learned numerous Unix commands such as, ls, cd, mkdir, rmdir, making files via "pico", and copying/moving files. We also set up both telnet and ftp software at our home computers to allow us to interact with both MHS and the AiS Challenge site.

We spent a week discussing general math algorithms for computing geometric shapes and computing distances and velocities in simple motion problems.

Next, we spent five weeks learning the basic concepts of C++ programming code. We learned concepts and programming skills such as setting up the main function, cout and cin commands, mathematical computations, for loops, the use of if-else, mod, and setting up arrays. Also, we used the math algorithms in a Unix machine as the basis of most of our programs. We combined the math algorithms with programming skills towards computing the volume and surface area of a sphere and solving physics problems of motion. We programmed over ten programs that compute different kinds of problems. Basically, our instructor provided us with ample information to write the program code for our project.

Initial Robotics Project (submitted as initial abstract)

Our first idea of a project didn't work out. We tried our best to do some research on this project, but there were no Internet sources on the idea. Our first idea was to compare the efficiency of programming code layers and the efficiency of a neural net in robots. We were planning to build two identical computer models of robots; except that one would use programming code and the other would use a neural net. For example, we were planning on graphing the motions and scrutinizing the efficiency of the simple tasks that the robots could accomplish. We would use this information to make a conclusion deciding which method of building artificial intelligence would be more affective, the programming layers or the neural net. We finally decided that pursuing this idea would be unfeasible since the idea is still being tested in professional laboratories. We wrote an abstract and did a plethora of research on the notion. However, we finally decided that the whole idea was too difficult to accomplish in the allotted time.

Predator and Prey Project (basis of Interim Report)

After deciding that our idea was flawed, our group and instructor quickly met and brainstormed for 50 minutes about finding a new idea. We finally decided on graphing a computer-simulated model of an ecosystem. We plan to use a graphical user interface to help us use Starlogo programming code to simulate our mathematical model. The ecosystem will consist of two types of dots on the screen. One color would simulate the predators in the system, and the other color would simulate the prey. There will be a larger number of prey dots than predator dots since that's how it is in a real ecosystem. Also, the prey dots will herd together, and both simulated species will reproduce according to the mathematical equation that we program. Every time a predator dot comes in the proximity of a prey dot, the predator dot will start chasing the prey dot, and then it'll disappear. However, every time two dots of the same type come in contact, a new dot is formed. We will also factor in such variables as natural selection, rate of movement, gender, and disease. In this case, natural selection is that every different dot, even of the same type, may have different sizes and rates of movement. Thus, only the best prey dots will survive the longest. Our main goal is to find the number of ideal dots of each type that would result in the longest lasting and most efficient ecosystem.

As of now, we are still working on presenting our idea to a panel of judges. Joe Evans is working on our program code in Starlogo; Si Do is creating our Power Point presentation; Brandon Bednarski is currently refining our web page, and I, Muhammad Dais, am writing this interim report. After our idea has been presented, we are hoping to find a mentor as soon as possible and begin pursuing our simulation of an ecosystem. We plan to use the course of the entire next semester to work on our project. Hopefully, it will be a success.


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