86 research outputs found
Learning-Based Synthesis of Safety Controllers
We propose a machine learning framework to synthesize reactive controllers
for systems whose interactions with their adversarial environment are modeled
by infinite-duration, two-player games over (potentially) infinite graphs. Our
framework targets safety games with infinitely many vertices, but it is also
applicable to safety games over finite graphs whose size is too prohibitive for
conventional synthesis techniques. The learning takes place in a feedback loop
between a teacher component, which can reason symbolically about the safety
game, and a learning algorithm, which successively learns an overapproximation
of the winning region from various kinds of examples provided by the teacher.
We develop a novel decision tree learning algorithm for this setting and show
that our algorithm is guaranteed to converge to a reactive safety controller if
a suitable overapproximation of the winning region can be expressed as a
decision tree. Finally, we empirically compare the performance of a prototype
implementation to existing approaches, which are based on constraint solving
and automata learning, respectively
Even shorter proofs without new variables
Proof formats for SAT solvers have diversified over the last decade, enabling
new features such as extended resolution-like capabilities, very general
extension-free rules, inclusion of proof hints, and pseudo-boolean reasoning.
Interference-based methods have been proven effective, and some theoretical
work has been undertaken to better explain their limits and semantics. In this
work, we combine the subsumption redundancy notion from (Buss, Thapen 2019) and
the overwrite logic framework from (Rebola-Pardo, Suda 2018). Natural
generalizations then become apparent, enabling even shorter proofs of the
pigeonhole principle (compared to those from (Heule, Kiesl, Biere 2017)) and
smaller unsatisfiable core generation.Comment: 21 page
The Way We Were: Structural Operational Semantics Research in Perspective
This position paper on the (meta-)theory of Structural Operational Semantic
(SOS) is motivated by the following two questions: (1) Is the (meta-)theory of
SOS dying out as a research field? (2) If so, is it possible to rejuvenate this
field with a redefined purpose?
In this article, we will consider possible answers to those questions by
first analysing the history of the EXPRESS/SOS workshops and the data
concerning the authors and the presentations featured in the editions of those
workshops as well as their subject matters.
The results of our quantitative and qualitative analyses all indicate a
diminishing interest in the theory of SOS as a field of research. Even though
`all good things must come to an end', we strive to finish this position paper
on an upbeat note by addressing our second motivating question with some
optimism. To this end, we use our personal reflections and an analysis of
recent trends in two of the flagship conferences in the field of Programming
Languages (namely POPL and PDLI) to draw some conclusions on possible future
directions that may rejuvenate research on the (meta-)theory of SOS. We hope
that our musings will entice members of the research community to breathe new
life into a field of research that has been kind to three of the authors of
this article.Comment: In Proceedings EXPRESS/SOS2023, arXiv:2309.0578
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