We are going to create agents for decision-making in deep and complex sequential environments with huge state spaces,
like Pluribus which beats top professional poker players in No-Limit Holdem poker with 10^161 states. We can do this
with combining following three main components

CFR Algorithms

For making decisions in environments with sequential structures, like games, specifically imperfect information games

• We are going ti implement different variations of CFR
  • Vanilla CFR
  • CFR+
  • Chance Sampling CFR
  • Linear CFR
  • MCCFR
  • Our improvements of CFR

Real time search and Depth Limited Solving in subgames

State space clustering and abstractions