Information about the participants of the 2nd Lichess Bots Championship

You can post information about your bot here so people get to know your bot and I can use the information when I write about the games and results of your bot.

A) Based on Fruit 2.1 (by Fabien Letouzey), it is in a state of development not significantly different from the original and, at least for now (and I believe that for some time ahead), we can say that for all intents and purposes it is a Fruit 2.1.

B)
º Win 7 (32 bits)
º P4, 2 CPU (3 GHz)
º 2 GB RAM

C) The interface with Lichess does not respond to commands given in chat messages.

Thank you, Hoplites. Others can also use A/B/C. It is also possible to use the ethercalc.org/71jfmfuu762m questions. I'll use this information when I post some statistics at the end of the tournament (and I just think it's very interesting to see the differences between the bots).

Written in Golang - source code available at github.com/hub2/chesser-go as a fun project to create engine that can beat it's creator(it succeeded already! :D)

Accepts challenges from anyone.
Uses 1 thread on Ubuntu 18.04, i7-4790k.

In development all the time, hopefully wants to see progress between this and next tournament as I add more and more features (threading is next big one)!

lc0 v20.1 - running on a GTX 1060, 3 cpu threads. Debating on which net to use, possibly 32585 or 11248. Suggestions would be appreciated :p

Using ethercalc.org/71jfmfuu762m:

1B
(2, 3)C
4B (correspondence) 4C (others)
(5, 6, 7)C
8B
(9, 10)C
11a
12b...12f
13c
(14, 15)C
16c
(17, 18, 19)C
20B
21C
22a
23a (others) 23d (correspondence)
24... ?? derived from an existing one?

1) Using LeelaChessZero with Perfect2017 opening book and tablebase. ID will be 32585 unless a better ID is announced/found by the Leela Community.
2) Running on Overclocked i5-6600K @ 4.1 GHZ and Overclocked GPU RTX 2070, Windows 10
3) LeelaChess is tuned for optimal play on my computer, if you want to know the specific command line opts passed to Leela, feel free to PM me.

Raven is an engine I wrote in Python. It uses the python-chess library for board representation, move generation and making/unmaking, and for opening book and endgame tablebase. It uses a negamax search with alpha beta pruning and quiescence search. It has a transposition table and uses iterative deepening. It also uses some basic move ordering for optimization.

It's running on a 1.7 Ghz Windows 10 laptop.

Toshiba Celeron 2.16GHz with single core.

Iterative deepening, transpositon tables, move ordering, quiescence search, piece square tables.
Works with 7 piece types: K, Q, R, B, N, WP and BP.
(White and black pawns are regarded as different pieces as they move in different directions.)
Board layout chosen so pawn moves increment or decrement square numbers, rather than the common +/- 8.

Some of the these decisions seemed to be very minor improvements at the time, but the reality is they make working with standard endgame tablebases etc more difficult.

Adding to #2: ponder (off); hash (16); openning book (yes).

Correcting #6: 22(a, b, c).

In ethercalc.org/71jfmfuu762m: I think 'pondering' is a relevant data to stay in this table.