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Constrained Reinforcement Learning (RL) aims to maximize the return while adhering to predefined constraint limits, which represent domain-specific safety requirements. In continuous control settings, where learning agents govern system…

Machine Learning · Computer Science 2025-09-12 Somnath Hazra , Pallab Dasgupta , Soumyajit Dey

Using the framework of boosting, we prove that all impurity-based decision tree learning algorithms, including the classic ID3, C4.5, and CART, are highly noise tolerant. Our guarantees hold under the strongest noise model of nasty noise,…

Machine Learning · Computer Science 2022-06-20 Guy Blanc , Jane Lange , Ali Malik , Li-Yang Tan

Automated theorem provers are used in extended static checking, where they are the performance bottleneck. Extended static checkers are run typically after incremental changes to the code. We propose to exploit this usage pattern to improve…

Logic in Computer Science · Computer Science 2007-08-07 Radu Grigore , Michał Moskal

In this contribution we revisit regular model checking, a powerful framework that has been successfully applied for the verification of infinite-state systems, especially parameterized systems (concurrent systems with an arbitrary number of…

Logic in Computer Science · Computer Science 2021-11-23 Anthony W. Lin , Philipp Rümmer

We extended our simulation tool Ntccrt for probabilistic ntcc (pntcc) models. In addition, we developed a verification tool for pntcc models. Using this tool we can prove properties such as the system will go to a successful state with…

Logic in Computer Science · Computer Science 2018-10-15 Mauricio Toro

We present a unified deductive verification framework for first-order temporal properties based on well-founded rankings, where verification conditions are discharged using SMT solvers. To that end, we introduce a novel reduction from…

Logic in Computer Science · Computer Science 2026-01-21 Raz Lotan , Neta Elad , Oded Padon , Sharon Shoham

The performance of a reinforcement learning algorithm can vary drastically during learning because of exploration. Existing algorithms provide little information about the quality of their current policy before executing it, and thus have…

Machine Learning · Computer Science 2019-05-29 Christoph Dann , Lihong Li , Wei Wei , Emma Brunskill

Large language models (LLMs) have demonstrated significant potential in formal theorem proving, yet state-of-the-art performance often necessitates prohibitive test-time compute via massive roll-outs or extended context windows. In this…

Machine Learning · Computer Science 2026-04-22 Guchan Li , Rui Tian , Hongning Wang

Formally verifying the correctness of mathematical proofs is more accessible than ever, however, the learning curve remains steep for many of the state-of-the-art interactive theorem provers (ITP). Deriving the most appropriate subsequent…

Logic in Computer Science · Computer Science 2024-11-05 Liao Zhang , David M. Cerna , Cezary Kaliszyk

The evaluation of logic locking methods has long been predicated on an implicit assumption that only the correct key can unveil the true functionality of a protected circuit. Consequently, a locking technique is deemed secure if it resists…

Cryptography and Security · Computer Science 2024-08-26 Yinghua Hu , Hari Cherupalli , Mike Borza , Deepak Sherlekar

The classical satisfiability problem (SAT) is used as a natural and general tool to express and solve combinatorial problems that are in NP. We postulate that provability for implicational intuitionistic propositional logic (IIPC) can serve…

Logic in Computer Science · Computer Science 2024-05-14 Aleksy Schubert , Paweł Urzyczyn , Konrad Zdanowski

In this paper, new contributions to requirements-based testing with deterministic finite state machines are presented. Elementary requirements are specified as triples consisting of a state in the reference model, an input, and the expected…

Software Engineering · Computer Science 2021-05-26 Wen-ling Huang , Jan Peleska

We study nested conditions, a generalization of first-order logic to a categorical setting, and provide a tableau-based (semi-decision) procedure for checking (un)satisfiability and finite model generation. This generalizes earlier results…

Logic in Computer Science · Computer Science 2024-07-10 Lara Stoltenow , Barbara König , Sven Schneider , Andrea Corradini , Leen Lambers , Fernando Orejas

We give a first account of our new parallel SAT solver Gimsatul. Its key feature is to share clauses physically in memory instead of copying them, which is the method of other state-of-the-art multi-threaded SAT solvers to exchange clauses…

Logic in Computer Science · Computer Science 2022-08-01 Mathias Fleury , Armin Biere

Model checkers use automated state exploration in order to prove various properties such as reachability, non-reachability, and bisimulation over state transition systems. While model checkers have proved valuable for locating errors in…

Logic in Computer Science · Computer Science 2015-08-03 Quentin Heath , Dale Miller

Language models can behave in unexpected and unsafe ways, and so it is valuable to monitor their outputs. Internal activations of language models encode additional information that could be useful for this. The baseline approach for…

Machine Learning · Computer Science 2025-04-30 Henk Tillman , Dan Mossing

In this paper, we explore the application of blocked clause elimination for projected model counting. This is the problem of determining the number of models ||\exists X.{\Sigma}|| of a propositional formula {\Sigma} after eliminating a…

Artificial Intelligence · Computer Science 2024-08-13 Jean-Marie Lagniez , Pierre Marquis , Armin Biere

This paper presents the verification of control systems implemented in Simulink. The goal is to ensure that high-level requirements on control performance, like stability, are satisfied by the Simulink diagram. A two stage process is…

Systems and Control · Computer Science 2021-04-13 Dejanira Araiza-Illan , Kerstin Eder , Arthur Richards

We study decidability of verification problems for timed automata extended with unbounded discrete data structures. More detailed, we extend timed automata with a pushdown stack. In this way, we obtain a strong model that may for instance…

Logic in Computer Science · Computer Science 2017-01-11 Karin Quaas

Scoring rules evaluate probabilistic forecasts of an unknown state against the realized state and are a fundamental building block in the incentivized elicitation of information. This paper develops mechanisms for scoring elicited text…

Artificial Intelligence · Computer Science 2025-11-13 Yifan Wu , Jason Hartline