STIT logic is a prominent framework for the analysis of multi-agent choice-making. In the available deontic extensions of STIT, the principle of Ought-implies-Can (OiC) fulfills a central role. However, in the philosophical literature a variety of alternative OiC interpretations have been proposed and discussed. This paper provides a modular framework for deontic STIT that accounts for a multitude of OiC readings. In particular, we discuss, compare, and formalize ten such readings. We provide sound and complete sequent-style calculi for all of the various STIT logics accommodating these OiC principles. We formally analyze the resulting logics and discuss how the different OiC principles are logically related. In particular, we propose an endorsement principle describing which OiC readings logically commit one to other OiC readings.
Incorrectness Separation Logic (ISL) is a proof system that is tailored specifically to resolve problems of under-approximation in programs that manipulate heaps, and it primarily focuses on bug detection. This approach is different from the over-approximation methods that are used in traditional logics such as Hoare Logic or Separation Logic. Although the soundness of ISL has been established, its completeness remains unproven. In this study, we establish relative completeness by leveraging the expressiveness of the weakest postconditions; expressiveness is a factor that is critical to demonstrating relative completeness in Reverse Hoare Logic. In our ISL framework, we allow for infinite disjunctions in disjunctive normal forms, where each clause comprises finite symbolic heaps with existential quantifiers. To compute the weakest postconditions in ISL, we introduce a canonicalization that includes variable aliasing.
As ergonomic and user-centered kitchen design gains importance, integrating built-in appliances such as refrigerators has become common in modern households. However, spatial misalignment and circulation conflicts often disrupt kitchen routines. This study introduces the BEHAVIOR model (Behavioral Embeddedness Evaluation for Appliance-Versatile Integrated Operation Routing), a multidimensional framework for evaluating the movement path adaptability of embedded refrigerators in integrated kitchen–dining environments. The model identifies eight behavioral dimensions: Body Clearance, Embedded Compatibility, Handling Logic, Accessibility, Visual Feedback, Interaction Conflict, Operating Time, and Routing Simplicity, from a user–space–product coordination perspective. Expert-based AHP weighting and user entropy methods were combined to construct adaptability scores across five kitchen layouts (L-shaped, U-shaped, single-line, G-shaped, and island). The findings indicate that Routing Simplicity and Accessibility are the core determinants of layout adaptability, while Operating Time and Body Space show layout-dependent variations. Interaction Conflict and Embedded Compatibility are significantly influenced by spatial compactness. This research identifies key behavioral bottlenecks in kitchen workflows and presents a scalable model for appliance–space compatibility analysis, contributing to behavioral product evaluation and highlighting the role of user dynamics in design decisions.
The article explores key challenges in the formation and development of digital sovereignty across the South Caucasus region. Adopting a political science perspective, it outlines the conceptual framework of the study, which focuses on assessing the level of digital advancement and sovereignty in the context of emerging regional security risks and threats. The analysis examines the institutional foundations underpinning digital infrastructure development in the region, offering an assessment of national readiness for digital transformation. Particular emphasis is placed on the legislative regulation of the digital sector, as well as on strategic approaches to digital development and sovereignty as reflected in national policy documents. The study demonstrates that the ongoing strategic competition between the “North-South” and “East-West” transport and logistics corridors in the South Caucasus also shapes the logic and geography of emerging digital routes. In this context, multilateral integration into international internet traffic corridors is identified as a critical challenge for diversifying access routes, enhancing national digital security, and strengthening digital sovereignty. The analysis of the logistical architecture of digital corridors - at both regional and macro-regional levels - enables the identification of the main barriers and prospects for digital integration in the South Caucasus. Methodologically, the study employs a cross-country comparative approach alongside quantitative measures of digitalization, including the Network Readiness Index, mobile and fixed internet penetration, and related indicators.
This interview was given in 2008 by Arkady Zakrevsky (1928–2014), Corresponding Member of the National Academy of Sciences of Belarus (1972), Doctor of Technical Sciences (1967), and Professor (1969). He stood at the origins of the birth of cybernetics in the Soviet Union. He proposed the programming language for logical tasks LYaPAS, on the basis of which a series of computer-aided design systems for discrete devices was created, and methods for implementing parallel algorithms for the logical control of interacting processes. Some monographs: LYaPAS: A Programming Language for Logic and Coding Algorithms (N.-Y., L.: Academic Press, 1969; with M. A. Gavrilov); Boolesche Gleichungen: Theorie, Anwendung, Algorithmen (Berlin: VEB Verlag Technik, 1984; with Dieter Bochmann and Christian Posthoff); Combinatorial Algorithms of Discrete Mathematics (Tallinn: TUT Press, 2008; with Yu. Pottosin, L. Cheremisinova); Optimization in Boolean Space (Tallinn: TUT Press, 2009; with Yu. Pottosin, L. Cheremisinova); Design of Logical Control Devices (Tallinn: TUT Press, 2009; with Yu. Pottosin, L. Cheremisinova); Combinatorial Calculations in Many-Dimensional Boolean Space (Tallinn: TUT Press, 2012); Solving Large Systems Logical Equations (Tallinn: TUT Press, 2013).
Gustavo A. Acosta-Amaya, Deimer A. Miranda-Montoya, Jovani A. Jimenez-Builes
(1) Background: Human detection and tracking are critical tasks for assistive autonomous robots, particularly in ensuring safe and efficient human–robot interaction in indoor environments. The increasing need for personal assistance among the elderly and people with disabilities has led to the development of innovative robotic systems. (2) Methods: This research presents a lightweight two-layer control architecture for a human-following robot, integrating a fuzzy behavior-based control system with low-level embedded controllers. The system uses an RGB-D sensor to capture distance and angular data, processed by a fuzzy controller to generate speed set-points for the robot’s motors. The low-level control layer was developed using pole placement and internal model control (IMC) methods. (3) Results: Experimental validation demonstrated that the proposed architecture enables the robot to follow a person in real time, maintaining the predefined following distance of 1.3 m in each of the five conducted trials. The IMC-based controller demonstrated superior performance compared to the pole placement controller across all evaluated metrics. (4) Conclusions: The proposed control architecture effectively addresses the challenges of human-following in indoor environments, offering a robust, real-time solution suitable for assistive robotics with limited computational resources. The system’s modularity and scalability make it a promising approach for future developments in personal assistance robotics.
We extend classical Propositional Logic (PL) by adding a new primitive binary connective $\varphi|ψ$, intended to represent the "superposition" of sentences $\varphi$ and $ψ$, an operation motivated by the corresponding notion of quantum mechanics, but not intended to capture all aspects of the latter as they appear in physics. To interpret the new connective, we extend the classical Boolean semantics by employing models of the form $\langle M,f\rangle$, where $M$ is an ordinary two-valued assignment for the sentences of PL and $f$ is a choice function for all pairs of classical sentences. In the new semantics $\varphi|ψ$ is strictly interpolated between $\varphi\wedgeψ$ and $\varphi\veeψ$. By imposing several constraints on the choice functions we obtain corresponding notions of logical consequence relations and corresponding systems of tautologies, with respect to which $|$ satisfies some natural algebraic properties such as associativity, closedness under logical equivalence and distributivity over its dual connective. Thus various systems of Propositional Superposition Logic (PLS) arise as extensions of PL. Axiomatizations for these systems of tautologies are presented and soundness is shown for all of them. Completeness is proved for the weakest of these systems. For the other systems completeness holds if and only if every consistent set of sentences is extendible to a consistent and complete one, a condition whose truth is closely related to the validity of the deduction theorem.
A central quest in explainable AI relates to understanding the decisions made by (learned) classifiers. There are three dimensions of this understanding that have been receiving significant attention in recent years. The first dimension relates to characterizing conditions on instances that are necessary and sufficient for decisions, therefore providing abstractions of instances that can be viewed as the "reasons behind decisions." The next dimension relates to characterizing minimal conditions that are sufficient for a decision, therefore identifying maximal aspects of the instance that are irrelevant to the decision. The last dimension relates to characterizing minimal conditions that are necessary for a decision, therefore identifying minimal perturbations to the instance that yield alternate decisions. We discuss in this tutorial a comprehensive, semantical and computational theory of explainability along these dimensions which is based on some recent developments in symbolic logic. The tutorial will also discuss how this theory is particularly applicable to non-symbolic classifiers such as those based on Bayesian networks, decision trees, random forests and some types of neural networks.
The aim of the work is the optimisation of a rail heater, constituted by a magnetic core supplied by a sinusoidal current, which induces an eddy current in the rail. Optimisation parameters are electrical and geometrical quantities: supply frequency, voltage amplitude, airgaps, and core shape, while objectives are power transferred to the rail, absorbed current, and power distribution index. Optimisation is performed by an accurate field analysis, provided by the finite element method (FEM), coupled to an automated multiobjective procedure based on fuzzy logic. Particular care has been devoted to the FEM model in order to take into account important phenomena as non-linearity magnetic behaviour and non-uniform distribution of current in the rail caused by eddy currents.
SAMANTA C. DE ARAUJO, ANA PAULA M. DI BENEDITTO, CARLOS EDUARDO N. GATTS
et al.
Abstract This study compares local ecological knowledge (LEK) of fishers from the Southwest Atlantic Ocean (SWAO), Brazil, related to the franciscana dolphin (Pontoporia blainvillei). We conducted 330 ethnographic interviews in ten fishing communities in southern and southeastern Brazil between 2012 and 2018. Boolean or Classic Logic was used to identify 95 fishers who were able to recognize the franciscana dolphin accordingly to the taxonomic entity P. blainvillei: 23 in northern Espírito Santo state, one in southern Espírito Santo, 20 in northern Rio de Janeiro state, and 51 in northern Paraná state. Among these 95 fishers, 87.4% (n = 83) reported incidental captures in fishing nets. Among these, 52 (54.7%) did not know any solution to this problem. Interviews revealed that the fishers usually discard carcasses in the sea after fat and muscle tissue are removed so that they can be used as bait for shark fishing or as food. In Southeastern Brazil, fishers LEK related to their ability to identify franciscana dolphin varied from ‘no identification’ and ‘extremely low identification’ to ‘partial’ and ‘good identification,’ while in southern Brazil, fishers mainly presented a ‘good identification’ of the dolphins. We propose comanagement actions to conserve the franciscana dolphin in the SWAO.
In this article we show that bi-intuitionistic predicate logic lacks the Craig Interpolation Property. We proceed by adapting the counterexample given by Mints, Olkhovikov and Urquhart for intuitionistic predicate logic with constant domains (G. Mints, G. K. Olkhovikov and A. Urquhart. Failure of Interpolation in Constant Domain Intuitionistic Logic. Journal of Symbolic Logic, 78: 937--950 (2013)). More precisely, we show that there is a valid implication $φ\rightarrow ψ$ with no interpolant (i.e. a formula $θ$ in the intersection of the vocabularies of $φ$ and $ψ$ such that both $φ\rightarrow θ$ and $θ\rightarrow ψ$ are valid). Importantly, this result does not contradict the unfortunately named `Craig interpolation' theorem established by Rauszer in (Cecylia Rauszer. Craig Interpolation Theorem for an Extention of Intuitionistic Logic. Bull. Ac. Pol. Sc., 25(4), 337--341 (1977)) since that article is about the property more correctly named `deductive interpolation' (see Galatos, Jipsen, Kowalski and Ono's use of this term in N. Galatos, P. Jipsen, T. Kowalski, \& H. Ono. Residuated Lattices: An Algebraic Glimpse at Substructural Logics. Studies in Logic and the Foundations of Mathematics, Vol. 151. Amsterdam: Elsevier B. V. (2007)) for global consequence. Given that the deduction theorem fails for bi-intuitionistic logic with global consequence, the two formulations of the property are not equivalent.
Sanzida Murshed, Amy L. Griffin, Md Ashraful Islam
et al.
This study developed a geo-spatial framework for assessing multi-hazard threat on the Bangladesh coast, integrating environmental hazards (EH), geo-environmental attributes (GA), and anthropogenic modifications (AM) based on their potential contribution to overall threat. For this purpose, a fuzzy logic based analytical technique was integrated with geospatial mapping. Thematic layers were prepared for twenty-three theoretically important factors representing the three components of threat. The spatial variations of threat and its components were delineated through spatial overlaying of the respective layers in a GIS environment. The final threat map revealed 32% (5338 km2) and 4% (646 km2) of the area of the western deltaic coast, which encompassed >50–60% of the areas of Khulna, Bagerhat, and Satkhira districts, was under high and very high threat, respectively, owing primarily to frequent cyclones, salinity ingression, and subsidence, and secondarily to the low elevation of the coast, high astronomical tide, shallow bathymetry, excessive groundwater extraction, and polder construction. High and very high threat zones within the central estuarine coast corresponded to 27% (4518 km2) and 16% (2618 km2) of the area, including most of Bhola, Barguna, and Patuakhali districts, which was attributable to the effects of coastal erosion, sea-level rise, flooding and the ancillary effects of strong wave action, high river discharge, deforestation, and land transformation. Around 14% (948 km2) and 3% (164 km2) of the eastern cliff coast, comprising the southwestern part of the Coxsbazar district, was found to be under high and very high threat, respectively, due to the direct effects of sea-level rise, storm surge, erosion, and indirect effects of closeness to the shoreline, alluvial composition of the beach, tourism, and pollution from industries. The outcomes of this study could guide the coastal managers of Bangladesh in prioritizing actions aimed at disaster risk reduction and sustainable development of this region.
M. Arshad Zahangir Chowdhury, Timothy E. Rice, Matthew A. Oehlschlaeger
Conventional black box machine learning (ML) algorithms for gas-phase species identification from THz frequency region absorption spectra have been reported in the literature. While the robust classification performance of such ML models is promising, the black box nature of these ML tools limits their interpretability and acceptance in application. Here, a one-dimensional convolutional neural network (CNN), VOC-Net, is developed and demonstrated for the classification of absorption spectra for volatile organic compounds (VOCs) in the THz frequency range, specifically from 220 to 330 GHz where prior experimental data is available. VOC-Net is trained and validated against simulated spectra, and also demonstrated and tested against experimental spectra. The performance of VOC-Net is examined by the consideration of confusion matrices and receiver-operator-characteristic (ROC) curves. The model is shown to be 99+% accurate for the classification of simulated spectra and 97% accurate for the classification of noisy experimental spectra. The model’s internal logic is examined using the Gradient-weighted Class Activation Mapping (Grad-CAM) method, which provides a visual and interpretable explanation of the model’s decision making process with respect to the important distinguishing spectral features.
Energy conservation is one of the main challenges hindering the advancement of Wireless Sensor Networks (WSNs) in the Internet of Things (IoT). Although various approaches including probabilistic, deterministic, and mixed model based solutions have been proposed to solve the issue of energy conservation in cluster based WSNs, most of them do not consider the node’s heterogeneity in terms of energy as well as transmission rate during the creation or selection of clusters. In this paper, a new Fairness Aware Clustering Scheme (FACS) for heterogeneous WSN is proposed, where we consider heterogeneity of the WS N in terms of transmission rate and energy. In contrast to existing schemes, the proposed FACS provides a set of polices that take care of round operations and improve the network performance and lifetime. In FACS, fuzzy logic is employed to benefit from the heterogeneity of the nodes and to determine the utility of each node. Through extensive simulation, we show that FACS performs efficiently and it outperforms the existing state-of-the-art approaches in terms of network lifespan, energy, and fairness.
Extending the popular Answer Set Programming (ASP) paradigm by introspective reasoning capacities has received increasing interest within the last years. Particular attention is given to the formalism of epistemic logic programs (ELPs) where standard rules are equipped with modal operators which allow to express conditions on literals for being known or possible, i.e., contained in all or some answer sets, respectively. ELPs thus deliver multiple collections of answer sets, known as world views. Employing ELPs for reasoning problems so far has mainly been restricted to standard decision problems (complexity analysis) and enumeration (development of systems) of world views. In this paper, we take a next step and contribute to epistemic logic programming in two ways: First, we establish quantitative reasoning for ELPs, where the acceptance of a certain set of literals depends on the number (proportion) of world views that are compatible with the set. Second, we present a novel system that is capable of efficiently solving the underlying counting problems required to answer such quantitative reasoning problems. Our system exploits the graph-based measure treewidth and works by iteratively finding and refining (graph) abstractions of an ELP program. On top of these abstractions, we apply dynamic programming that is combined with utilizing existing search-based solvers like (e)clingo for hard combinatorial subproblems that appear during solving. It turns out that our approach is competitive with existing systems that were introduced recently. This work is under consideration for acceptance in TPLP.
Annalisa Liccardo, Francesco Bonavolontà, Ignazio Romano
et al.
Ensuring service continuity has become a fundamental issue for companies involved in electricity distribution; in particular, isolating the smallest possible portion of the network as a result of faults has long been a primary objective. To this aim, solutions based on logic selectivity have been defined and implemented for an efficient search for the network branch affected by the fault and its subsequent isolation. The authors have recently presented a proposal for the implementation of logic selectivity that exploits the LoRa transmission protocol, an ideal solution in the case of areas not reachable by the currently exploited communication technologies. The present paper, instead, deals with the optimization of some LoRa parameters, which made it possible to exploit network configurations in terms of coverage range, sensitivity and signal-to-noise ratio. The performance of the new configuration has been assessed through a number of tests conducted in the laboratory and on-field, highlighting promising results in terms of both intervention times and reliability. In particular, tests conducted in both rural and urban areas have assured fault isolation times as low as 33 ms (fully compliant with the current regulations) in the presence of the most challenging fault condition.
To increase plant productivity, greenhouse buildings are needed that can protect plants from external factors and integrated with smart systems that can be monitored anytime and anywhere, and can provide optimal plant needs automatically. In this research, a system was built that can monitor greenhouse conditions in real time anywhere through Blynk application with IoT concept, as well as a system that can control output automatically with fuzzy logic method. The focus of control on this research is the duration of watering with Mini Water Pump and light intensity setting with LED Strip. This system is also equipped with FAN that can be active when the temperature is 31°C or more. Parameters used in this system are DHT22 sensor (air temperature and humidity), Soil Moisture sensor, Water Level sensor ,LDR sensor (light intensity) and RTC DS3231 (Real Time Clock), which is controlled with Arduino Mega 2560 microcontroller. In the test results obtained accuracy on fuzzy logic water pump by 93.1% and accuracy on fuzzy logic LED Strip by 99.6%. In the test results of the existing parameters, the results get a fairly optimal reading.
The provability logic of a theory T is the set of modal formulas, which under any arithmetical realization are provable in T . We slightly modify this notion by requiring the arithmetical realizations to come from a specified set $Γ$. We make an analogous modification for interpretability logics. This is a paper from 2012. We first studied provability logics with restricted realizations, and show that for various natural candidates of theory T and restriction set $Γ$, where each sentence in $Γ$ has a well understood (meta)-mathematical content in T, the result is the logic of linear frames. However, for the theory Primitive Recursive Arithmetic (PRA), we define a fragment that gives rise to a more interesting provability logic, by capitalizing on the well-studied relationship between PRA and I$Σ_1$. We then study interpretability logics, obtaining some upper bounds for IL(PRA), whose characterization remains a major open question in interpretability logic. Again this upper bound is closely relatively to linear frames. The technique is also applied to yield the non-trivial result that IL(PRA) $\subset$ ILM.