How many times have your elders given you advice based on something they have experienced? “Well, when I was your age…”, “Back in my day, we did it like this…” It might seem like an annoying parental quirk, but it’s not that far off from the approach scientists, educators, and even computer algorithms use to solve problems.
Case-based reasoning is any kind of problem-solving approach that uses past solutions to solve similar problems. It assumes that knowledge can be acquired through past experiences, and can help warn you of avenues that will lead to failure or to help you think of successful past solutions that could be adapted to the problem at hand.
Case-based reasoning is all around us. For example, Google Maps uses case-based reasoning to tell you how long your journey will take by examining the patterns of past users to see how long it took them to get from point A to point B. Even if your path is from two slightly different points, it makes inferences on how long your journey will take.
Case-based reasoning can range from simpler tasks to complex computer algorithms. On one hand, it can be used to figure out something as simple as a cookie recipe. If you’re a fan of Friends, you may remember the episode where Monica tries to recreate Phoebe’s grandmother’s chocolate chip cookie recipe. She uses the failures of past batches to figure out a new solution to the problem, similar to a trial-and-error system.
On the more complex side of things, computers use a similar method to Monica. They categorize past problems and their solutions into ‘cases’, and then calculate how similar those cases are to the current problem to come up with a solution. This algorithm is common to examine patterns, diagnosis, trouble-shooting and planning.1