Constraint Satisfaction Methods Research Articles

Рассуждения с темпоральными ограничениями

The work deals with the organization of temporal reasoning basing on constraint satisfaction methods. The definition of the constraint satisfaction problem and the notion of constraint consistency are given. The possibilities of epresentation of a planning problem as an interval constraint network are considered. As a mathematical apparatus for the formalization of temporal reasining, the Allen’s interval algebra is described, which main operations are composition and the intersection of temporal relations. A path consistency algorithm is given that implements one of the types of local consistency on interval constraint network and uses computations based on operations of interval algebra. An example of the application of this algorithm is presented. In the conclusion the prospects for the development of methods of temporal reasoning are considered.

COSMOS: A comprehensive framework for automatically generating domain-oriented test suite

Coverage criteria are satisfied by at least one examination of the test target, while many faults are not revealed by one execution. However, despite executing the faulty statement, the test result is correct in certain circumstances. Such coincidentally passing test cases execute the faulty statement but do not cause failures. This paper introduces the new concept of domain solver. Domain solvers attempt to detect the domain of inputs rather than a single input satisfying a path constraint. Domain coverage is a new metric to evaluate the relative accuracy of the detected domains. The promising point is that the proposed approach similarly treats nonlinear and linear constraints. Domain solver splits a path constraint into conjunctions of simple conditions comparing two expressions. Such a splitting simplifies the constraint-solving task to detect regions of the input space satisfying a comparison between two expressions. After finding a region, an improved version of an algorithm, update, is used to determine the domain of variables involved in the comparing expressions. Our proposed approach, COSMOS, is implemented using the Roslyn compiler. We compared COSMOS with well-known constraint solvers using various linear/nonlinear constraints. The results show that COSMOS improves the number of supported data types involved in a constraint and solves100% of the instances in which the other solvers fail. Besides, COSMOS achieves the best relative accuracy of 84% compared to the existing domain-oriented test suite generation approaches. Moreover, our experiment results illustrate that COSMOS improves the fault-finding capability of other existing test coverage criteria by detecting coincidentally correct test cases. Combining domain coverage and compiler as a service makes a powerful constraint satisfaction method outperforming the existing constraint solvers regarding the number of solved linear/nonlinear constraints. Augmenting other structural test coverage criteria with domain coverage reveals the coincidentally correct test cases.

On the enumeration of finite 𝐿-algebras

We use Constraint Satisfaction Methods to construct and enumerate finite L L -algebras up to isomorphism. These objects were recently introduced by Rump and appear in Garside theory, algebraic logic, and the study of the combinatorial Yang–Baxter equation. There are 377,322,225 isomorphism classes of L L -algebras of size eight. The database constructed suggests the existence of bijections between certain classes of L L -algebras and well-known combinatorial objects. We prove that Bell numbers enumerate isomorphism classes of finite linear L L -algebras. We also prove that finite regular L L -algebras are in bijective correspondence with infinite-dimensional Young diagrams.

Enumeration of set-theoretic solutions to the Yang–Baxter equation

We use Constraint Satisfaction methods to enumerate and construct set-theoretic solutions to the Yang–Baxter equation of small size. We show that there are 321,931 involutive solutions of size nine, 4,895,272 involutive solutions of size ten and 422,449,480 non-involutive solution of size eight. Our method is then used to enumerate non-involutive biquandles.

Static Equivalence Checking for OpenFlow Networks

Software-defined networking (SDN) provides many advantages over traditional networking by separating the control and data planes. One of the advantages is to provide programmability, which allows administrators to control the behavior of the network. The network configuration may need to be changed for some reason. Whenever such changes are made, it can be required to verify that the forwarding behavior is preserved from the existing configuration, that is, whether the ruleset is properly reflected. In this paper, we propose the forwarding behavior based equivalence checking of OpenFlow networks. We present the formal definition of the network model and the forwarding behavior of the packet flow. Based on the definition, We present a method for checking the equivalence of OpenFlow network forwarding behaviors. Next, we present the implementation of the proposed method, using the constraint satisfaction method, which will be the basis for further extension.

Algorithmic Verification of Constraint Satisfaction Method on Timetable Problem

Various problems in the real world can be viewed as the Constraint Satisfaction Problem (CSP) based on several mathematical principles. This paper is a guideline for complete automation of the Timetable Problem (TTP) formulated as CSP, which we are able to solve algorithmically, and so the advantage is the possibility to solve the problem on a computer. The theory presents fundamental concepts and characteristics of CSP along with an overview of basic algorithms used in terms of its solution and forms the TTP as CSP and delineates the basic properties and requirements to be met in the timetable. The theory in our paper is mostly based on the Jeavons, Cohen, Gyssens, Cooper, and Koubarakis work, on the basis of which we've constructed a computer programme, which verifies the validity and functionality of the Constraint satisfaction method for solving the Timetable Problem. The solution of the TTP, which is characterized by its basic characteristics and requirements, was implemented by a tree-based search algorithm to a program and our main contribution is an algorithmic verification of constraints abilities and reliability when solving a TTP by means of constraints. The created program was also used to verify the time complexity of the algorithmic solution.

A recommender system based on personal constraints for smart tourism city

ABSTRACT In a smart tourism ecosystem, travel communication websites play a critical role in choosing destinations and hotels. This research suggests a travel recommender system for automating word-of-mouth (WOM) effects and providing personalized travel-planning services to tourists. Collaborative filtering (CF)-based recommender systems have been extensively employed for personalization services in diverse areas; the basic principle of CF is WOM communication. This research proposes a travel recommender system that helps a tourist build his/her personalized travel plan based on CF and constraint satisfaction filtering. Constraint satisfaction filtering is adopted to profile a tourist’s needs and circumstances. For this purpose, this research modifies the existing constraint satisfaction method to an approximate constraint satisfaction filtering method that incorporates indifference intervals into constraints. We build a prototype system and a benchmark system to evaluate the effectiveness, usability, and novelty of the proposed travel recommender system. The experimental results demonstrate a methodology for performing personalized tourist’s travel planning and automating WOM communication outperforms the benchmark system.

Preliminary design of a 100\xa0MW-net ocean thermal energy conversion (OTEC) power plant study case: Mentawai island, Indonesia

Ocean thermal energy conversion is one of the promising renewable energy resources yet relatively unexplored due to its high capital cost for being utilized in commercial scale. In the aim to reduce the capital cost, this paper introduces a concept design of the floating structure from a converted oil tanker ship. To propose the design process, the general principles of designing a converted tanker FPSO is adapted and then modified to deal with ocean thermal energy conversion (OTEC) characteristic. In the design process, the arrangement of the OTEC layout is carried out by constraint satisfaction method and the prospective floating structure size is varied using Monte Carlo simulation. The variables in the design process consist of the velocities of cold water and warm water transport, the size of the plantship, and the location of the OTEC equipment to the seawater tank. Constraints are introduced as allowable border to determine the acceptability for particular case including the provided space and buoyancy, and the net power output estimation. The results show that the ‘typical’ size of a Suezmax oil tanker ship is the optimum one for the plantship with the velocity of the water transport of 2–3 m/s. The general arrangement is also conceptualized in this paper.

Toward a Mature Science of Consciousness.

In Being No One, Metzinger (2004[2003]) introduces an approach to the scientific study of consciousness that draws on theories and results from different disciplines, targeted at multiple levels of analysis. Descriptions and assumptions formulated at, for instance, the phenomenological, representationalist, and neurobiological levels of analysis provide different perspectives on the same phenomenon, which can ultimately yield necessary and sufficient conditions for applying the concept of phenomenal representation. In this way, the “method of interdisciplinary constraint satisfaction (MICS)” (as it has been called by Weisberg, 2005) promotes our understanding of consciousness. However, even more than a decade after the first publication of Being No One, we still lack a mature science of consciousness. This paper makes the following meta-theoretical contribution: It analyzes the hurdles an approach such as MICS has yet to overcome and discusses to what extent existing approaches solve the problems left open by MICS. Furthermore, it argues that a unifying theory of different features of consciousness is required to reach a mature science of consciousness.

Mereotopological Correction of Segmentation Errors in Histological Imaging

In this paper we describe mereotopological methods to programmatically correct image segmentation errors, in particular those that fail to fulfil expected spatial relations in digitised histological scenes. The proposed approach exploits a spatial logic called discrete mereotopology to integrate a number of qualitative spatial reasoning and constraint satisfaction methods into imaging procedures. Eight mereotopological relations defined on binary region pairs are represented as nodes in a set of 20 directed graphs, where the node-to-node graph edges encode the possible transitions between the spatial relations after set-theoretic and discrete topological operations on the regions are applied. The graphs allow one to identify sequences of operations that applied to regions of a given relation, and enables one to resegment an image that fails to conform to a valid histological model into one that does. Examples of the methods are presented using images of H&E-stained human carcinoma cell line cultures.

Structural synthesis of complex electrotechnical equipment on the basis of the constraint satisfaction method

This article deals with structural synthesis of complicated electric power systems. The main draw-back is stated of existing approaches to automated performance of structural synthesis requiring time-consuming software algorithms to find solutions, and a support software tool is developed to take into account changes in the method of calculation. Constraint satisfaction problems related to the problem of configuration synthesis are formulated, and its features are highlighted. The synthesis problem is adopted to obtain a valid configuration in accordance with the requirements and approaches to optimal configuration characteristics in accordance with a predetermined objective function. An overview is given of existing methods of finding solution, and their characteristics are analyzed. A method is described of structural synthesis based on constraint satisfaction. Ways are examined to improve the effectiveness of the methods by applying a combination of heuristics in a solution-finding algorithm. The main features of an algorithm that is developed based on a local search algorithm are given. One feature of the algorithm is a search strategy in the subspace unacceptable and subspace acceptable solutions subspaces. A way to use the method that has been developed is proposed.

A Parameter Estimation Method for Dynamic Computational Cognitive Models

A dynamic computational cognitive model can be used to explore a selected complex cognitive phenomenon by providing some features or patterns over time. More specifically, it can be used to simulate, analyse and explain the behaviour of such a cognitive phenomenon. It generates output data in the form of time series which can only be partially compared to empirical knowledge. This leads to a challenging problem to estimate values of the parameters of the model representing characteristics of a person. A parameter estimation approach for dynamic cognitive models is presented here by combining improved Particle Swarm Optimization (PSO) and Constraint Satisfaction (CS) methods. Having collected the key features of behaviour of a phenomenon, those are translated into a set of constraints with parameters that will be solved through an improved agent based PSO technique. Through this, within PSO each agent explores the complex search space while communicating the quality of a local parameter value vector relative to their current global best solution as a swarm (through cooperation and competition). This is performed in tournaments and results of each tournament are combined to address the premature convergence issue in PSO.

List Superstructures and Semantics of Iterators

Based on the GES (Goncharov–Ershov–Sviridenko) theory of list superstructures [1, 2], we study the semantics of iterators which is used in the object iterated programming language Libretto [3]. We note that Libretto also allows us to give a strong logic interpretation and can be used for constructing and managing object oriented databases [4]. One of the main difficulties is to organize nondeterministic computations related to input collections of elements satisfying a certain condition. Iterators can be represented as a realization of bounded existential quantifier ∃x ∈ M.F (x). A basic “intrinsic” iterator in Libretto is responsible for the strategy of depthfirst search. However, there are other iterators simulating more delicate strategies for looking for solutions related, for example, with methods of constraint satisfaction [5]. In particular, it is of interest to consider iterators simulating semantic programming on finite domains [6]. Based on the Σ-definability of inductive definitions [7, 8] in the GES theory, it is possible to model recursive descriptions without additional constructions like fixed point operators. In this paper, we use this property of the GES theory coming back to the theory of admissible sets [9].

A constraint satisfaction method applied to the problem of controlling the CO2 emission in the Legal Brazilian Amazon

Socioeconomic-driven processes such as deforestation, forest degradation, forest fires, overgrazing, overharvesting of fuelwood and slash-and-burn practices constitute the primary sources of Greenhouse Gases (GHG) emissions in developing countries. Climate policies can induce the development of clean technology and offer incentives to accelerate reforestation. The Brazilian government has already acknowledged the urgency to invest in policies to reduce anthropogenic CO2 emissions in the Legal Brazilian Amazon (BA). In this work, we propose a scheme to estimate the required investments in clean technology and reforestation to achieve a prescribed short term target value for the atmospheric CO2 emission. Initially, a mathematical model is fitted to the available data to allow forecasting the values of the short term emissions of CO2 under a combination of investments in clean technology and reforestation. The investments to reduce the emissions of CO2 below a target value (400 million tons/year, starting at the initial value of 450) in 3 years’ time are proportional to the regional GDP. Using computer simulation it is possible to generate a range of possible investment values in clean technology and reforestation, so that the prescribed emission reduction is achieved without hindering economic growth. This strategy provides the necessary investment flexibility for the implementation of realistic climate policies.

Research on Fuzzy-logic Algorithm of Intelligent Generating Test Paper

Intelligent generating test paper can be thought of as a typical fuzzy mathematical logic problem. First, the paper analyzes the quantitative evaluation criteria of the traditional test paper generation questions and shows the existing problems in practical application of it. Then the paper introduces two different fuzzy constraints principal disjunctive normal form concept and proposes an evaluation system combining quantitative with qualitative. Viewing at the particularity of constraint satisfaction problems of intelligent generating test paper, the paper uses heuristic knowledge and applies constraint satisfaction method combining generation test with membership correction constraint satisfaction methods to realize intelligent generating test paper. The experiment shows that this method obtains good results.

A first-principles-based correlation functional for harmonious connection of short-range correlation and long-range dispersion

We present a physically motivated correlation functional belonging to the meta-generalized gradient approximation (meta-GGA) rung, which can be supplemented with long-range dispersion corrections without introducing double-counting of correlation contributions. The functional is derived by the method of constraint satisfaction, starting from an analytical expression for a real-space spin-resolved correlation hole. The model contains a position-dependent function that controls the range of the interelectronic correlations described by the semilocal functional. With minimal empiricism, this function may be adjusted so that the correlation model blends with a specific dispersion correction describing long-range contributions. For a preliminary assessment, our functional has been combined with an atom-pairwise dispersion correction and full Hartree-Fock (HF)-like exchange. Despite the HF-exchange approximation, its predictions compare favorably with reference interaction energies in an extensive set of non-covalently bound dimers.

A Generic Approach to Challenge Modeling for the Procedural Creation of Video Game Levels

This paper presents an approach to automatic video game level design consisting of a computational model of player enjoyment and a generative system based on evolutionary computing. The model estimates the entertainment value of game levels according to the presence of “rhythm groups,” which are defined as alternating periods of high and low challenge. The generative system represents a novel combination of genetic algorithms (GAs) and constraint satisfaction (CS) methods and uses the model as a fitness function for the generation of fun levels for two different games. This top-down approach improves upon typical bottom-up techniques in providing semantically meaningful parameters such as difficulty and player skill, in giving human designers considerable control over the output of the generative system, and in offering the ability to create levels for different types of games.

A Provably High-Probability White-Space Satisfaction Algorithm With Good Performance for Standard-Cell Detailed Placement

In this paper, we propose an effective white-space (i.e., row length) constraint satisfaction technique embedded in a network flow based detailed placer for standard cell designs that is suitable for both incremental as well as full detailed placement. The highlight of our method is a provable high-probability of obtaining a legal placement even under tight white space (WS) constraints. This high success probability of our method stems from our flexibility of allowing a well-controlled temporary WS constraint violation in the detailed placement process. The flexibility also helps improve the solution quality of the detailed placer, measured by the deterioration of the optimization metric from the global placement solution. We tested our WS constraint-satisfaction method controlled temporary violations (CTV) on two sets of benchmarks for both incremental and full placement applications, and for timing as well as wire length (WL) optimization problems. We obtained legal solutions for all circuits in reasonable times under a 3% WS constraint. For example, for a 210 k-cell circuit td-ibm18: 1) for the timing-driven incremental placement application, we obtain the final placement in 900 secs with a 35.2% delay reduction compared to an initial WL-optimized placement done by Dragon 2.23 and 2) for the full timing-driven placement problem, we obtain the final placement in less than 2.5 h with a timing improvement of 29.8% compared to the state-of-the-art WL-driven detailed placer of NTUplace3-LE. We also tested two internal methods, one that disallows any temporary WS violation, and another which moves cells from WS violated rows to non-full rows in a heuristic manner. The first method cannot legalize all benchmarks, and CTV is 41%-86% relatively better in delay and WL metrics than the two internal methods.

Constraint-Based Personalization For Business Applications

This paper reports on extensions of previous work applying personalization techniques and constraint-based methods within an intelligent agent framework. The Wise Net Inc. has developed an intelligent agent framework specifically for providing advanced scalable collaborative capabilities for easy integration with existing web-enabled enterprise applications. Since the summer of 2001, the author, his colleagues, and his research assistants, have been conducting applied research aimed at discovering the desired personalization models and effects to support collaborative e-business systems. Intelligent agents are being developed to implement these personalization effects through constraint-satisfaction methods and solvers. This paper documents the approach, progress achieved to date, and future directions. This work is being supported by The Wise Net Inc., the BC Advanced Systems Institute (BC ASI), and the Canadian National Research Council (NRC) through the Industrial Research Assistance Program (IRAP).

An Interval-based Constraint Satisfaction (IBCS) Method for Decentralized, Collaborative Multifunctional Design

Set-based design has been proposed as a strategy for multifunctional design problems where stakeholders from different disciplines strive to achieve domain-specific objectives while sharing a set of design variables. This strategy involves communicating information about sets of alternatives in contrast to communicating information about a single alternative at a time. The strategy has been developed for collaborative CAD and for selection among design alternatives during conceptual design, it has not been implemented as a computational method for decentralized collaborative multi-objective design problems. In this article, we address this research gap by presenting an Interval-Based Constraint Satisfaction (IBCS) Method for decentralized, collaborative multifunctional design. The method is based on transforming a decentralized multifunctional design problem into a constraint satisfaction problem by using non-cooperative game theoretic protocols. The resulting constraint satisfaction problem is then solved using interval-based consistency techniques. A non-cooperative game theory protocol is utilized in this method because it reflects the level of information exchange possible in a distributed environment. Central to this protocol is the representation of a Rational Reaction Set (RRS) that encapsulates a designer's decision-making strategy as a constraint in the design space. An intersection of all designers' RRSs represents a solution to the overall multifunctional design problem. We use interval-based consistency techniques, specifically box consistency, to sequentially eliminate regions of design space that do not satisfy the individual RRSs, thereby progressively narrowing the design space in order to reduce computational complexity in arriving at a solution. This method stands in marked contrast to the successive consideration of single solution points, as emphasized in existing multifunctional design methods. The key advantages of the proposed method are: (a) gradual reduction of design freedom and (b) non-divergence of solutions. The method is illustrated using two sample scenarios — the solution of a decision problem with quadratic objectives and the design of multifunctional Linear Cellular Alloys (LCAs).