pokerb wrote:
Awesome! Love the project and love the github profile pic. Thanks for sharing, I'll certainly take a deeper peek through it. So your library is largely built for the decision making aspect, or the stats that could drive effective decision making?
Yes, for now it's only
1. Game abstraction :
- bucketting the cards state (based on *HS, also implemented OCHS)
- building a reduced betting tree (so I have a module that implements the NL betting rules)
- putting them together to have a walkable game tree
2. Computing data for decision making :
- HS, EHS, EHS2 (also used for bucketting)
- CS-CFRM
pokerb wrote:
I've also segmented everything purposefully, with dedicated classes to manage different models and states of the overall game, and dedicated classes for actions such as scraping, clicking, odds, and even decision making. Drawback at the moment is I've written everything in objective-c, but I'm comfortable with that and don't plan on transitioning away for the moment. Not sure yet if I'll open source, for the moment it's still very experimental. Perhaps I'll open source the decision making part as a compilable library that anyone can plug in and experiment with. I've learnt a ton in the process, and have many ideas to sharpen it further. Hope the results keep up!
Nice Happy coding Statistics: Posted by Pitt — Sun Jun 04, 2017 9:23 am
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