926 research outputs found
Language and Proofs for Higher-Order SMT (Work in Progress)
Satisfiability modulo theories (SMT) solvers have throughout the years been
able to cope with increasingly expressive formulas, from ground logics to full
first-order logic modulo theories. Nevertheless, higher-order logic within SMT
is still little explored. One main goal of the Matryoshka project, which
started in March 2017, is to extend the reasoning capabilities of SMT solvers
and other automatic provers beyond first-order logic. In this preliminary
report, we report on an extension of the SMT-LIB language, the standard input
format of SMT solvers, to handle higher-order constructs. We also discuss how
to augment the proof format of the SMT solver veriT to accommodate these new
constructs and the solving techniques they require.Comment: In Proceedings PxTP 2017, arXiv:1712.0089
Encoding TLA+ set theory into many-sorted first-order logic
We present an encoding of Zermelo-Fraenkel set theory into many-sorted
first-order logic, the input language of state-of-the-art SMT solvers. This
translation is the main component of a back-end prover based on SMT solvers in
the TLA+ Proof System
Goal Translation for a Hammer for Coq (Extended Abstract)
Hammers are tools that provide general purpose automation for formal proof
assistants. Despite the gaining popularity of the more advanced versions of
type theory, there are no hammers for such systems. We present an extension of
the various hammer components to type theory: (i) a translation of a
significant part of the Coq logic into the format of automated proof systems;
(ii) a proof reconstruction mechanism based on a Ben-Yelles-type algorithm
combined with limited rewriting, congruence closure and a first-order
generalization of the left rules of Dyckhoff's system LJT.Comment: In Proceedings HaTT 2016, arXiv:1606.0542
Learning-Assisted Automated Reasoning with Flyspeck
The considerable mathematical knowledge encoded by the Flyspeck project is
combined with external automated theorem provers (ATPs) and machine-learning
premise selection methods trained on the proofs, producing an AI system capable
of answering a wide range of mathematical queries automatically. The
performance of this architecture is evaluated in a bootstrapping scenario
emulating the development of Flyspeck from axioms to the last theorem, each
time using only the previous theorems and proofs. It is shown that 39% of the
14185 theorems could be proved in a push-button mode (without any high-level
advice and user interaction) in 30 seconds of real time on a fourteen-CPU
workstation. The necessary work involves: (i) an implementation of sound
translations of the HOL Light logic to ATP formalisms: untyped first-order,
polymorphic typed first-order, and typed higher-order, (ii) export of the
dependency information from HOL Light and ATP proofs for the machine learners,
and (iii) choice of suitable representations and methods for learning from
previous proofs, and their integration as advisors with HOL Light. This work is
described and discussed here, and an initial analysis of the body of proofs
that were found fully automatically is provided
Premise Selection and External Provers for HOL4
Learning-assisted automated reasoning has recently gained popularity among
the users of Isabelle/HOL, HOL Light, and Mizar. In this paper, we present an
add-on to the HOL4 proof assistant and an adaptation of the HOLyHammer system
that provides machine learning-based premise selection and automated reasoning
also for HOL4. We efficiently record the HOL4 dependencies and extract features
from the theorem statements, which form a basis for premise selection.
HOLyHammer transforms the HOL4 statements in the various TPTP-ATP proof
formats, which are then processed by the ATPs. We discuss the different
evaluation settings: ATPs, accessible lemmas, and premise numbers. We measure
the performance of HOLyHammer on the HOL4 standard library. The results are
combined accordingly and compared with the HOL Light experiments, showing a
comparably high quality of predictions. The system directly benefits HOL4 users
by automatically finding proofs dependencies that can be reconstructed by
Metis
Computer Science and Metaphysics: A Cross-Fertilization
Computational philosophy is the use of mechanized computational techniques to
unearth philosophical insights that are either difficult or impossible to find
using traditional philosophical methods. Computational metaphysics is
computational philosophy with a focus on metaphysics. In this paper, we (a)
develop results in modal metaphysics whose discovery was computer assisted, and
(b) conclude that these results work not only to the obvious benefit of
philosophy but also, less obviously, to the benefit of computer science, since
the new computational techniques that led to these results may be more broadly
applicable within computer science. The paper includes a description of our
background methodology and how it evolved, and a discussion of our new results.Comment: 39 pages, 3 figure
Verified AIG Algorithms in ACL2
And-Inverter Graphs (AIGs) are a popular way to represent Boolean functions
(like circuits). AIG simplification algorithms can dramatically reduce an AIG,
and play an important role in modern hardware verification tools like
equivalence checkers. In practice, these tricky algorithms are implemented with
optimized C or C++ routines with no guarantee of correctness. Meanwhile, many
interactive theorem provers can now employ SAT or SMT solvers to automatically
solve finite goals, but no theorem prover makes use of these advanced,
AIG-based approaches.
We have developed two ways to represent AIGs within the ACL2 theorem prover.
One representation, Hons-AIGs, is especially convenient to use and reason
about. The other, Aignet, is the opposite; it is styled after modern AIG
packages and allows for efficient algorithms. We have implemented functions for
converting between these representations, random vector simulation, conversion
to CNF, etc., and developed reasoning strategies for verifying these
algorithms.
Aside from these contributions towards verifying AIG algorithms, this work
has an immediate, practical benefit for ACL2 users who are using GL to
bit-blast finite ACL2 theorems: they can now optionally trust an off-the-shelf
SAT solver to carry out the proof, instead of using the built-in BDD package.
Looking to the future, it is a first step toward implementing verified AIG
simplification algorithms that might further improve GL performance.Comment: In Proceedings ACL2 2013, arXiv:1304.712
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