Quote:
Originally Posted by smurfgirl
I think design elements can play into how successful a robot and/or an alliance is. For example, if an alliance is comprised of three robots which can only collect balls from a payload specialist, won't this have an impact on the dynamics of that alliance? They will frequent certain areas of the field more often, perhaps stopping in front of them often for short periods of time. Similarly, wouldn't you want to know if this was true of an opposing team an/or alliance? Knowing things about design elements can help you to strategize for your alliance, as well as to try to predict what an opposing alliance will do.
Also, how do you figure that accuracy is not important for success? If a particular team only scores about 5% of the game pieces they attempt to score... isn't that a way of measuring how successful they are at their offensive maneuvers? Would you choose a team like this to play offense on your alliance? Would this data affect the way you strategize against an opposing alliance?
|
It does happen to affect how well the robot performs, yes, but knowledge of it it isn't necessary to select the best robot, since accuracy isn't an economic good in this game. If a robot can only score 5% of the time, I wouldn't choose them not because of the 5% number, I wouldn't choose them because they simply fail to score enough points period. Likewise if they break down continuously, this will affect the total number of game pieces scored and affect the choice accordingly. Accuracy is not a limited good, neither is robustness, but time and game pieces are, and thus you need only be concerned with how efficiently the robot uses them if you are selecting alliance partners (selection of partners is all I was concerned with).
You are right, I did almost completely neglect the strategy element (I only really study the qualification numbers, I should put up a disclaimer, actual implementation will vary by needs). For instance, knowing a robot has Ackerman steering is an exploitable weakness that can reduce its overall effectiveness during a game. Knowing the different autonomous modes it has can help too. I have found it difficult to come up with objective data that would be useful, and have tended to ignore those points altogether and leave strategy to someone else in the pits. In any case I'll be sure to keep a better eye on strategy this season
