Mosquitos 10/3

Group 1:

    Tim: lights add the barrier to a stack of problems to solve. Program then tries to find the endpoint. If the end point connects to a new barrier, it will add that onto the stack. A future strategy will break the board into grids based on the barriers and add a light to the section. Not convinced with the strategy of lights going to highest mosquito density
    Franklin: to place the collector in the grid strategy, put it in between sections. Planning on using other data structures to help calculate the different sections
    Vishwa: avoiding the obstacles strategy is unaffected by the number of lights. When you are trying to move around the barriers you can cut of mosquitoes following you. to fix this they are planning on creating a buffer to keep the mosquitoes

Group 2:

    Jinesh: Wanted to keep with the sweeping strategy. Trying to make a circuit to cover the board. The key to this is to intelligently place the nodes on the board.
    Tieram: Noticed that there are two aspects, one where are the mosquitoes, and two how to analyze the board with the obstacles. Tries to  pre-analyze the board and use these to sweep the board. Using a minimum spanning tree, to place the collector. You can have a lot of issues with repeating work, maybe set up a circuit for the lights. Currently setting up nodes by the ends of the barriers to avoid losing mosquitos.
    Di: <Not in class>

Group 3

    Harjot: three parts of the strategy, target, acquisition & collection;  Placing the collector is very simple right now, either in the center or in an empty space.
    Tanveer: using a variation of A* with the barriers. Find an optimal strategy between the start and end point for each light using waypoints. The waypoints are placed based on the end points of the obstacles. waypoints are calculated at the beginning based on the obstacles. 
    Hao

Group 4

    Sam: Is thinking of dividing up the board into better quadrants. Using mosquito density to avoid going back into a squares that have already been hit, but maybe a different indicator might be better. 
    Patrick: realized that it would be very hard to make a dynamic program work. Thinking about using A* and divide up the grid into quadrants
    Hari: Make the lights closest to the most populated area collect all the mosquitoes and then use A* to figure out the best path to the collector

Group 5

    Marcus: A* nodes are each 1 unit square. Have a buffer size around the ends of the barriers. 
    Tanay - The change in capture target percentage should maybe affect strategy. Need to optimize the A* since it takes a long time.     Will recalculate where to send the light after it gets to the collector. Want to better place the lights depending on population and barriers
    Lauren: kept greedy strategy, but added A*. Had the problem of going too close to walls, so are keeping track of the walls too. Once the light has hit the collector, the lights will go the most populated area that another light is not already going through. The lights stay off until it gets there.

Group 6
    Yigit: <not in class>
    Yang: The lights start from edges then go to the center where the collector is. It will then go back out the the most populated area. Lights are randomly placed on the board. Pre-computes paths the the lights to take to get to each area of the board using Dykstra’s algorithm.