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20132021
most citedDuality in STRIPS planning

3 citations · 6 across the 5 of their papers we have counts for

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cs.AI2021

Improving ENIGMA-Style Clause Selection While Learning From History

Martin Suda

We re-examine the topic of machine-learned clause selection guidance in saturation-based theorem provers. The central idea, recently popularized by the ENIGMA system, is to learn a…

cs.AI2021

Vampire With a Brain Is a Good ITP Hammer

Martin Suda

Vampire has been for a long time the strongest first-order automatic theorem prover, widely used for hammer-style proof automation in ITPs such as Mizar, Isabelle, HOL, and Coq. In…

cs.AI2020

ENIGMA Anonymous: Symbol-Independent Inference Guiding Machine (system description)

Jan Jakubův, Karel Chvalovský, Miroslav Olšák +3

We describe an implementation of gradient boosting and neural guidance of saturation-style automated theorem provers that does not depend on consistent symbol names across problems…

cs.AI2019

ENIGMA-NG: Efficient Neural and Gradient-Boosted Inference Guidance for E

Karel Chvalovský, Jan Jakubův, Martin Suda +1

We describe an efficient implementation of clause guidance in saturation-based automated theorem provers extending the ENIGMA approach. Unlike in the first ENIGMA implementation wh…

cs.AI2016

Selecting the Selection

Giles Reger, Martin Suda, Andrei Voronkov +1

Modern saturation-based Automated Theorem Provers typically implement the superposition calculus for reasoning about first-order logic with or without equality. Practical implement…

cs.AI20133 cited

Duality in STRIPS planning

Martin Suda

We describe a duality mapping between STRIPS planning tasks. By exchanging the initial and goal conditions, taking their respective complements, and swapping for every action its p…