This page features lessons on different techniques on approaching selection based scenarios with a special focus on budgeting systems.  We explore various approaches, show the key ideas for applying each, and give commentary/suggestions on what would be best.

**Note the audio was distorted when recording these lessons.  Apologies if the lessons are louder/more distorted than usual.**

This video lesson explores the very basic approaches component selection.  If very little time is available, these can be sometimes useful.  However, these techniques often rely heavily on luck and rarely give good solutions to QR2 scenarios.  Unless no other options exists teams should use the methods in the next videos to get good solutions (though those take more time and effort)

This important lesson focuses on the techniques that milowda recommend students use when trying to solve a QR2 style scenario.  This method analyses patterns and uses those patterns to make informed decisions on the best selections.  This method takes some time, but almost always can be applied to check nearly all configurations within the competition time.  While this method does not always give the exact score, it can still often identify the best solutions. 

This lesson shows how one can go about solving the scenario completely and (if no mistakes are made) allow one to correctly predict their score/the ideal solution.  While this is a powerful and tempting technique, it is prohibitively TIME CONSUMING and prone fail with even small errors.  In real life, this approach is used when absolute confidence is required and usually takes months of analysis and checking to verify the results.  Therefore, it is very difficult to achieve within the regular competition times and not suggested as goal for competing teams.  Your mileage may vary.