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Jakub Ciesluk

dblp:422/7328 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2026
—ORCID · none

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

Artificial intelligence and machine learning · 1 · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1 · 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%
Theoretical computer science
1 paper
Automata and formal languages · 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 playing
general game playing
1.012026
Regular Games - an Automata-Based General Game Playing Language · AAAI 2026
Automata and formal languages
finite automata
1.012026
Regular Games - an Automata-Based General Game Playing Language · AAAI 2026

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

procedural content generation · 2.0
YearPublicationVenuePosition
2026 Regular Games - an Automata-Based General Game Playing Language
abstract
We propose a new General Game Playing (GGP) system called Regular Games (RG). The main goal of RG is to be both computationally efficient and convenient for game design. The system consists of several languages. The core component is a low-level language that defines the rules by a finite automaton. It is minimal with only a few mechanisms, which makes it easy for automatic processing (by agents, analysis, optimization, etc.). The language is universal for the class of all finite turn-based games with imperfect information. Higher-level languages are introduced for game design (by humans or Procedural Content Generation), which are eventually translated to a low-level language. RG generates faster forward models than the current state of the art, beating other GGP systems (Regular Boardgames, Ludii) in terms of efficiency. Additionally, RG's ecosystem includes an editor with LSP, automaton visualization, benchmarking tools, and a debugger of game description transformations.
Radoslaw Miernik, Marek Szykula, Jakub Kowalski, Jakub Ciesluk, Lukasz Galas, Wojciech Pawlik
AAAI4