Allie is a strong engine that's looking competitive with the top ones (Leela Chess Zero and Stockfish). It's supposedly based off AlphaZero, but works differently. As far as I understand it, the most important difference is the search algorithm. The author said in a March 2019 interview that:
AT: To begin the tournament, Allie will perform MCTS based search with absolute fpu where new nodes start off with win pct of -1. The search is modeled after Deepminds paper’s. As I said above, I’m hoping to switch to AlphaBeta for the long term direction of the project. I’ve experimented with many, many ways of doing this with the networks generated by the Lc0 project and I think I’ve hit upon a way to achieve the depths required to maintain ELO level with MCTS based search, but it is not ready yet. In the future, I imagine we’ll see a lot of experimentation with different variations of search (mcts, ab) + eval (handwritten, NN) in computer chess engines. Hoping to be a part of that and to contribute to the shared pool of knowledge.
(Emphasis mine.) As of time of writing the Allie Github page says:
Well, I was inspired during the original CCC to see if you could pair traditional Minimax/AlphaBeta search with an NN. This is still her main purpose and the focus going forward. However, the initial versions were using a similar pure MCTS algorithm as Lc0 and AlphaZero. The current versions of Allie use a modified hybrid search of Minimax and Monte Carlo.
I don't understand what "modified hybrid search of Minimax and Monte Carlo" means. Can someone explain? I know what each of these terms mean, but I don't understand the combination.