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We introduce the concept of inverse feasibility for linear forward models as a tool to enhance OTA FL algorithms. Inverse feasibility is defined as an upper bound on the condition number of the forward operator as a function of its…

Machine Learning · Statistics 2024-05-27 Tomasz Piotrowski , Rafail Ismayilov , Matthias Frey , Renato L. G. Cavalcante

We derive an intuitionistic version of G\"odel-L\"ob modal logic ($\sf{GL}$) in the style of Simpson, via proof theoretic techniques. We recover a labelled system, $\sf{\ell IGL}$, by restricting a non-wellfounded labelled system for…

Logic in Computer Science · Computer Science 2023-09-04 Anupam Das , Iris van der Giessen , Sonia Marin

Consider a problem where a set of feasible observations are provided by an expert and a cost function is defined that characterizes which of the observations dominate the others and are hence, preferred. Our goal is to find a set of linear…

Optimization and Control · Mathematics 2020-09-14 Kimia Ghobadi , Houra Mahmoudzadeh

Conventional methods for query autocompletion aim to predict which completed query a user will select from a list. A shortcoming of this approach is that users often do not know which query will provide the best retrieval performance on the…

Information Retrieval · Computer Science 2022-04-26 Adam Block , Rahul Kidambi , Daniel N. Hill , Thorsten Joachims , Inderjit S. Dhillon

We present a new system S for handling uncertainty in a quantified modal logic (first-order modal logic). The system is based on both probability theory and proof theory. The system is derived from Chisholm's epistemology. We concretize…

Artificial Intelligence · Computer Science 2018-05-29 Naveen Sundar Govindarajulu , Selmer Bringsjord

Reinforcement learning has shown promise in learning policies that can solve complex problems. However, manually specifying a good reward function can be difficult, especially for intricate tasks. Inverse reinforcement learning offers a…

Machine Learning · Computer Science 2017-11-28 Peter Henderson , Wei-Di Chang , Pierre-Luc Bacon , David Meger , Joelle Pineau , Doina Precup

Bi-intuitionistic logic is the conservative extension of intuitionistic logic with a connective dual to implication. It is sometimes presented as a symmetric constructive subsystem of classical logic. In this paper, we compare three sequent…

Logic in Computer Science · Computer Science 2011-01-31 Luís Pinto , Tarmo Uustalu

Sequential propositional logic deviates from ordinary propositional logic by taking into account that during the sequential evaluation of a propositional statement,atomic propositions may yield different Boolean values at repeated…

Logic in Computer Science · Computer Science 2011-06-28 J. A. Bergstra , A. Ponse

Automated theorem provers (ATPs) can disprove conjectures by saturating a set of clauses, but the resulting saturated sets are opaque certificates. In the unit equational fragment, a saturated set can in fact be read as a convergent rewrite…

Logic in Computer Science · Computer Science 2026-02-19 Mikoláš Janota , Michael Rawson , Stephan Schulz

We present constructive provability logic, an intuitionstic modal logic that validates the L\"ob rule of G\"odel and L\"ob's provability logic by permitting logical reflection over provability. Two distinct variants of this logic, CPL and…

Logic in Computer Science · Computer Science 2012-05-30 Robert J. Simmons , Bernardo Toninho

This paper considers the problem of assumptions refinement in the context of unrealizable specifications for reactive systems. We propose a new counterstrategy-guided synthesis approach for GR(1) specifications based on Craig's…

Logic in Computer Science · Computer Science 2018-11-01 Davide G. Cavezza , Dalal Alrajeh

In this work we describe a new learning-based proof guidance -- ENIGMAWatch -- for saturation-style first-order theorem provers. ENIGMAWatch combines two guiding approaches for the given-clause selection implemented for the E ATP system:…

Artificial Intelligence · Computer Science 2019-08-26 Zarathustra Goertzel , Jan Jakubův , Josef Urban

It is commonly agreed that the success of future proof assistants will rely on their ability to incorporate computations within deduction in order to mimic the mathematician when replacing the proof of a proposition P by the proof of an…

Logic in Computer Science · Computer Science 2007-07-10 Frédéric Blanqui , Jean-Pierre Jouannaud , Pierre-Yves Strub

Our paper introduces a novel method for calculating the inverse $\mathcal{Z}$-transform of rational functions. Unlike some existing approaches that rely on partial fraction expansion and involve dividing by $z$, our method allows for the…

Optimization and Control · Mathematics 2024-06-11 MohammadJavad Vaez , Alireza Hosseini , Kamal Jamshidi

Recent advances in Automated Theorem Proving have shown the effectiveness of leveraging a (large) language model that generates tactics (i.e. proof steps) to search through proof states. The current model, while trained solely on successful…

Artificial Intelligence · Computer Science 2024-07-31 Chenyang An , Zhibo Chen , Qihao Ye , Emily First , Letian Peng , Jiayun Zhang , Zihan Wang , Sorin Lerner , Jingbo Shang

We recently described a formalism for reasoning with if-then rules that re expressed with different levels of firmness [18]. The formalism interprets these rules as extreme conditional probability statements, specifying orders of magnitude…

Artificial Intelligence · Computer Science 2013-03-25 Moises Goldszmidt , Judea Pearl

Decision analysis deals with modeling and enhancing decision processes. A principal challenge in improving behavior is in obtaining a transparent description of existing behavior in the first place. In this paper, we develop an expressive,…

Machine Learning · Statistics 2023-10-31 Daniel Jarrett , Alihan Hüyük , Mihaela van der Schaar

In reductive proof search, proofs are naturally generalized by solutions, comprising all possibly infinite structures generated by locally correct, bottom-up application of inference rules. We propose an extension of the Curry-Howard…

Logic in Computer Science · Computer Science 2021-07-30 José Espírito Santo , Ralph Matthes , Luís Pinto

We present a new algorithm for probabilistic planning with no observability. Our algorithm, called Probabilistic-FF, extends the heuristic forward-search machinery of Conformant-FF to problems with probabilistic uncertainty about both the…

Artificial Intelligence · Computer Science 2011-11-02 C. Domshlak , J. Hoffmann

Large-scale pre-trained language models have demonstrated strong capabilities of generating realistic text. However, it remains challenging to control the generation results. Previous approaches such as prompting are far from sufficient,…

Computation and Language · Computer Science 2021-11-10 Xu Zou , Da Yin , Qingyang Zhong , Ming Ding , Hongxia Yang , Zhilin Yang , Jie Tang