What's rather tricky about this whole problem is that every observable you are using is an output from a model. So even if you are privy to full information, know exactly which hands they have, these actions are but a single expression of how this model is behaving in a particular instance. This model's behavior may be very complex. It may include randomization. It's behavior undoubtedly depends on the opponents and context. This model can change. It may suddenly change as the person gets tired, angry or irrational. It can evolve, improve and learn from it's mistakes.
And as if that wasn't hard enough you don't even have the luxury of good, representative or holistic data at any given point in time.
This problem is starting to look really hard.
And yet I know this game isn't that hard, and that I do a pretty good job of figuring out how my opponents play. I can read my opponents; I can read their patterns and reverse engineer their psyche and have -- through thought and experience -- found those tell-tale signs that all players exhibit. The rhythms of failure, the sudden slips and tailspins into tilt or the gallops of great players finding their stride.
Is what I do hard? What is it my brain is finding when it sees these patterns? And how have I made money at poker in the past?
For one, though I paint a picture of a moving target, that target doesn't tend to be that hard or complex...
More thoughts later.
Subscribe to:
Post Comments (Atom)
No comments:
Post a Comment