1. Computer Systems Lab TJHSST Current Projects In-House, pt 2

2. 2 Current Projects, pt. 2 In-House Robot Swarms Modeling Evolutionary Behavior Developing a Learning Agent for Bridge Modeling the Physics of a Bowling Ball Optimization of a Traffic Signal

3. 3 Robot Swarms My project is an agent based simulation, posing robots in a “game of life”, with each new generation of robot comes new genes using a random number selection process creating the mutations and evolutions that in real life we experience for DNA cross over and such.

4. 4 Modeling Evolutionary Behavior The purpose of this project is to attempt to model evolutionary behavior in agents in an environment by introducing traits and characteristics that change with the different generations of agents. I hope to create an environment where certain agents will prosper and reproduce while others will have traits that negatively affect their performance. In the end, a single basic agent will evolve into numerous subspecies of the original agent and demonstrate evolutionary behavior.

5. 5 Developing a Learning Agent The goal of this project was to create a learning agent for the game of bridge. I think my current agent, which knows the rules, plays legally, and finds some basic good plays, is a step in the right direction. This agent could and will be improved upon over the course of the year and will become smarter and learn faster throughout the year

6. 6 Modeling a Bowling Ball The idea behind this project is to create a model of the dynamical bowling game system. By analyzing sets of physics equations and applying them to this system, a program can be created to calculate and output the path and other characteristics of a bowling ball's traversal across a bowling lane. This ouput is based on a set of initial conditions, including speed, angle, lane conditions, and starting rotation.

7. 7 Optimization of a Traffic Signal The purpose of this project is to produce an intelligent transport system (ITS) that controls a traffic signal in order to achieve maximum traffic throughput at the intersection. To produce an accurate model of the traffic flow, it is necessary to have each car be an autonomous agent with its own driving behavior. A learning agent will be used to optimize a traffic signal for the traffic of the autonomous cars.