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Tomás Cízek

dblp:146/5342 · DBLP profile ↗
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2ranked-venue papers
2as first author
2since 2021 · last 2026
0000-0002-0586-8082ORCID · verified

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 first-author · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author · 1 since 2021Theory of computation · 1 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Planning, search and constraint satisfaction · 100%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Parallel and multicore computing · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Knowledge, reasoning and agents › Planning, search and constraint satisfaction
game tree search
1.012026
Massively Parallel Proof-Number Search for Impartial Games and Beyond · AAAI 2026
Parallel and multicore computing › parallel algorithms
parallel search
1.012026
Massively Parallel Proof-Number Search for Impartial Games and Beyond · AAAI 2026

Methods — techniques the papers use, named apart from their topics

proof-number search · 2.0grundy numbers · 2.0
YearPublicationVenuePosition
2026 Massively Parallel Proof-Number Search for Impartial Games and Beyond
abstract
Proof-Number Search is a best-first search algorithm with many successful applications, especially in game solving. As large-scale computing clusters become increasingly accessible, parallelization is a natural way to accelerate computation. However, existing parallel versions of Proof-Number Search are known to scale poorly on many CPU cores. Using two parallelized levels and shared information among workers, we present the first massively parallel version of Proof-Number Search that scales efficiently even on a large number of CPUs. We apply our solver, enhanced with Grundy numbers for reducing game trees of impartial games, to the Sprouts game, a case study motivated by the long-standing Sprouts Conjecture. Our algorithm achieves 332.9x speedup on 1024 cores, significantly improving previous parallelizations and outperforming the state-of-the-art Sprouts solver GLOP by four orders of magnitude in runtime while generating proofs 1,000x more complex. Despite exponential growth in game tree size, our solver verified the Sprouts Conjecture for 42 new positions, nearly doubling the number of known outcomes.
Tomás Cízek, Martin Balko
AAAI1
2021 Implementation of Sprouts: A Graph Drawing Game
Tomás Cízek, Martin Balko
GD1