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SAI: a Sensible Artificial Intelligence that plays with handicap and
  targets high scores in 9x9 Go (extended version)
v1v2v3 (latest)

SAI: a Sensible Artificial Intelligence that plays with handicap and targets high scores in 9x9 Go (extended version)

26 May 2019
F. Morandin
G. Amato
M. Fantozzi
R. Gini
C. Metta
Maurizio Parton
    LLMAG
ArXiv (abs)PDFHTML

Papers citing "SAI: a Sensible Artificial Intelligence that plays with handicap and targets high scores in 9x9 Go (extended version)"

5 / 5 papers shown
Title
Increasing biases can be more efficient than increasing weights
Increasing biases can be more efficient than increasing weights
C. Metta
M. Fantozzi
Andrea Papini
G. Amato
Matteo Bergamaschi
S. Galfrè
Alessandro Marchetti
Michelangelo Vegliò
Maurizio Parton
F. Morandin
47
4
0
03 Jan 2023
Score vs. Winrate in Score-Based Games: which Reward for Reinforcement
  Learning?
Score vs. Winrate in Score-Based Games: which Reward for Reinforcement Learning?
Luca Pasqualini
G. Amato
Maurizio Parton
R. Gini
Alessandro Marchetti
C. Metta
F. Morandin
M. Fantozzi
44
2
0
31 Jan 2022
Derived metrics for the game of Go -- intrinsic network strength
  assessment and cheat-detection
Derived metrics for the game of Go -- intrinsic network strength assessment and cheat-detection
A. Egri-Nagy
Antti Törmänen
GNN
69
5
0
03 Sep 2020
Self-Play Learning Without a Reward Metric
Self-Play Learning Without a Reward Metric
Dan Schmidt
N. Moran
Jonathan S. Rosenfeld
Jonathan Rosenthal
J. Yedidia
72
4
0
16 Dec 2019
Accelerating Self-Play Learning in Go
Accelerating Self-Play Learning in Go
David J. Wu
103
96
0
27 Feb 2019
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