Computer Go has long been regarded as a challenge to computers, and it was only recently that Google’s AlphaGo achieved success playing a Go master. Strangely, however, the challenges of getting a computer to play Go well are similar to some of those faced in data analytics:
Go players have to recognise a number of types of scenarios – sets of features that together constitute a particular threat or opportunity. This, conceptually, is very similar to the scenarios that Scenario Analytics aims to find.
Computers can play both Chess and Go using an algorithm called “mini-max” (as well as its refinements such as alpha-beta search and Monte-Carlo search), which, in essence says “if I play any of these moves, you could reply with any of those moves, I could counter with any of…” down to some depth.
Theorems: A theorem is a generally Do we use the same code in Go, Chess, and our analytics? No, of course not, but we do use the same concepts.