Constraint Satisfaction Mechanism Research Articles

Interactive CAD Layout of Reflection-Based Mirror Metrology Systems

Concentrating solar mirrors need to accurately focus sunlight onto a receiver. Since mirror surface normal determines reflected light direction, reflection-based metrology methods that measure surface normal have the advantage of directly measuring the mirror’s intended functional performance characteristic. Several methods have been reported that produce high-resolution measurements of mirror surface normal of concentrating solar mirrors [1-8]; these systems typically employ an optical target, a camera, and sometimes an external light source. These elements must be placed in a configuration that satisfies multiple feasibility constraints, including mechanical and optical visibility and reflection constraints. For complex problems or installations in cluttered environments, it can be difficult to analyze all of these constraints manually. We have created a computer automated design (CAD) tool that aids in visualization of reflection-based metrology systems, making it possible to determine layouts for complex metrology design problems. The tool is implemented SolidWorks, a commercial CAD system [9]. By exploiting the SoidWorks constraint satisfaction mechanism, the tool is able to present interactive visualization of reflection and field of view constraints in real time without any additional code or macros. The tool supports ease of use and multiple design configurations through an ordinary spreadsheet interface. The tool can be used to address a variety of reflection-based metrology design problems, and is available to the public as open source.

Deep Constraint-Based Propagation in Graph Neural Networks.

The popularity of deep learning techniques renewed the interest in neural architectures able to process complex structures that can be represented using graphs, inspired by Graph Neural Networks (GNNs). We focus our attention on the originally proposed GNN model of Scarselli et al. 2009, which encodes the state of the nodes of the graph by means of an iterative diffusion procedure that, during the learning stage, must be computed at every epoch, until the fixed point of a learnable state transition function is reached, propagating the information among the neighbouring nodes. We propose a novel approach to learning in GNNs, based on constrained optimization in the Lagrangian framework. Learning both the transition function and the node states is the outcome of a joint process, in which the state convergence procedure is implicitly expressed by a constraint satisfaction mechanism, avoiding iterative epoch-wise procedures and the network unfolding. Our computational structure searches for saddle points of the Lagrangian in the adjoint space composed of weights, nodes state variables and Lagrange multipliers. This process is further enhanced by multiple layers of constraints that accelerate the diffusion process. An experimental analysis shows that the proposed approach compares favourably with popular models on several benchmarks.

Constraint satisfaction mechanisms for marginal stability and criticality in large ecosystems.

We discuss a resource-competition model, which takes MacArthur's model as a platform, to unveil interesting connections with glassy features and jamming in high dimensions. This model, as first studied by Tikhonov and Monasson, presents two qualitatively different phases: a shielded phase, where a collective, self-sustained behavior emerges, and a vulnerable phase, where a small perturbation can destabilize the system and contribute to population extinction. We first present our perspective based on a strong similarity with continuous constraint satisfaction problems in their convex regime. Then, we discuss the stability analysis in terms of the computation of the leading eigenvalue of the Hessian matrix of the associated Lyapunov function. This computation allows us to efficiently distinguish between the two aforementioned phases and to relate high-dimensional critical ecosystems to glassy phenomena in the low-temperature regime.

Holonic coordination obtained by joining the contract net protocol with constraint satisfaction

Present manufacturing systems are facing significant challenges concerning their adaptability. Holonic manufacturing systems are among the technologies that can provide solutions to such requests, if certain conditions are met. As being included in the class of semi-heterarchical control architectures, holonic systems need appropriate coordination and planning schemes, together with validation tools to increase the beneficiaries’ trust. This paper proposes a coordination scheme for holonic systems, based on a mix between contract net protocol and distributed constraint satisfaction problems. The distinct phases of this method are explained, with details referring to the adaptation of contract net protocol. About the constraint satisfaction mechanism, a guide is provided on how a manufacturing problem can be expressed according to this formalism. To validate the introduced coordination scheme, a coloured Petri net model was developed. This allowed several simulation experiments for scenarios regarding a manufacturing system with four robots to be carried out. The obtained solutions showed that the proposed method can determine both the right holarchy related to the manufacturing goal, and optimal plans for robots. Moreover, as proven by the reachability graphs obtained for different goals, the proposed method reached correct results for all goals and diverse constraints, and it determined all possible solutions. An advantage is about how knowledge possessed by different types of holons is efficiently used, without producing an increased communication load. In conclusion, our method can ensure the right trade-off between complexity and optimality, and the attached model can constitute the required link between design and implementation, thus contributing to an easier deployment of holonic systems.

Theoretical aspects of the chiShona passive

ABSTRACTThis paper analyses passivisation in chiShona within the Head-Driven Phrase Structure Grammar (HPSG) theoretical framework. We treat passives as operations on the argument structure of a verb, represented as a nested list just like causatives. We describe passive typology and explicate its morpho-syntactic characteristics with regards to complex predication. We conclude, in contradistinction to the valence altering causative counterpart that, though passives are complex morphologically, on the overall, they are not complex predicates. Our conclusions are based on the unavailability of aktionsart alternations, lack of event modification and the inability to be accounted for through argument composition. We reveal that chiShona intransitives passivise, which is evidence that passivisation is a backgrounding rather than foregrounding operation. We examine the relationship between passives and causatives, discovering that different passivisation possibilities are available, which depend on whether the causative type is morphological or periphrastic. Well-formed constructions are accounted for through HPSG formalism and the semantic meta-theory Lexical Resource Semantics constraint satisfaction mechanisms.

ChiShona periphrastic causatives as syntactic complex predicates: An HPSG analysis

This article examines the syntactico-semantic structure of periphrastic causatives in chiShona, a southern Bantu language spoken mainly in Zimbabwe. We argue that periphrastic causatives involve complex predication and are monoclausal. Evidence from scope related clause bound aspects in the form of negation, reflexivization, object and subject marking and passivization is used to corroborate the monoclausality. We utilise analytical insights from the notion of Argument Composition (AC) and Head-Driven Phrase Structure Grammar (HPSG) theory. Since AC is considered as a lexical process, its account of complex predicates satisfies strict compositionality whilst at the same time maintaining lexical integrity. Through the constraint satisfaction mechanisms of HPSG and the embedded semantic meta-theory of Lexical Resource Semantics (LRS) we provide evidence for the well-formedness of feature structures of periphrastic causatives in chiShona. We also demonstrate that as complex predicates, these causatives satisfy both the general and specific principles of both theories. The main argument that is proffered in this article is that through AC, the periphrastic causative shares much in common with its morphological counterpart, especially in the areas of valence, argument structure and lexical and compositional semantics.

The Theory of Reasoned Action as Parallel Constraint Satisfaction: Towards a Dynamic Computational Model of Health Behavior

The reasoned action approach, although ubiquitous in health behavior theory (e.g., Theory of Reasoned Action/Planned Behavior), does not adequately address two key dynamical aspects of health behavior: learning and the effect of immediate social context (i.e., social influence). To remedy this, we put forth a computational implementation of the Theory of Reasoned Action (TRA) using artificial-neural networks. Our model re-conceptualized behavioral intention as arising from a dynamic constraint satisfaction mechanism among a set of beliefs. In two simulations, we show that constraint satisfaction can simultaneously incorporate the effects of past experience (via learning) with the effects of immediate social context to yield behavioral intention, i.e., intention is dynamically constructed from both an individual’s pre-existing belief structure and the beliefs of others in the individual’s social context. In a third simulation, we illustrate the predictive ability of the model with respect to empirically derived behavioral intention. As the first known computational model of health behavior, it represents a significant advance in theory towards understanding the dynamics of health behavior. Furthermore, our approach may inform the development of population-level agent-based models of health behavior that aim to incorporate psychological theory into models of population dynamics.

Detection and resolution of semantic inconsistency and redundancy in an automatic ontology merging system

In recent years, researchers have been developing algorithms for the automatic mapping and merging of ontologies to meet the demands of interoperability between heterogeneous and distributed information systems. But, still state-of-the-art ontology mapping and merging systems is semi-automatic that reduces the burden of manual creation and maintenance of mappings, and need human intervention for their validation. The contribution presented in this paper makes human intervention one step more down by automatically identifying semantic inconsistencies in the early stages of ontology merging. We are detecting semantic heterogeneities that occur due to conflicts among the set of Generalized Concept Inclusions, Property Subsumption Criteria, and Constraint Satisfaction Mechanism in local heterogeneous ontologies, which become obstacles for the generation of semantically consistent global merged ontology. We present several algorithms to detect such semantic inconsistencies based on subsumption analysis of concepts and properties in local ontologies from the list of initial mappings. We provide ontological patterns for resolving these inconsistencies automatically. This results global merged ontology free from `circulatory error in class/property hierarchy', `common class between disjoint classes/properties', `redundancy of subclass/subproperty of relations' and other types of `semantic inconsistency' errors. Experiments on the real ontologies show that our algorithms save time and cost of traversing local ontologies, improve system's performance by producing only consistent accurate mappings, and reduce the users' dependability for ensuring the satisfiability of merged ontology.

Jamming with Plunderphonics: Interactive concatenative synthesis of music

This paper proposes to use the techniques of Concatenative Sound Synthesis in the context of real-time Music Interaction. We describe a system that generates an audio track by concatenating audio segments extracted from pre-existing musical files. The track can be controlled in real-time by specifying high-level properties (or constraints) holding on metadata about the audio segments. A constraint-satisfaction mechanism, based on local search, selects audio segments that best match those constraints at any time. We describe the real-time aspects of the system, notably the asynchronous adding/removing of constraints, and report on several constraints and controllers designed for the system. We illustrate the system with several application examples, notably a virtual drummer able to interact with a human musician in real-time.

Structural Dynamics of Cognition: From Consistency Theories to Constraint Satisfaction

We first offer a brief review of the history of cognitive consistency theories in social psychology. After promising beginnings as an outgrowth of Gestalt theory, early consistency theories failed to yield a general account of the mechanisms by which attitudes are formed and decisions are made. However over the past decade the principles underlying consistency theories have been revived in the form of connectionist models of constraint satisfaction. We then review experimental work on complex legal decision making that illustrates how constraint satisfaction mechanisms can cause coherence shifts, thereby transforming ambiguous inputs into coherent decisions.

Structural Dynamics of Cognition: From Consistency Theories to Constraint Satisfaction

We first offer a brief review of the history of Cognitive Consistency Theories in social psychology. After promising beginnings as an outgrowth of Gestalt theory, early consistency theories failed to yield a general account of the mechanisms by which attitudes are formed and decisions are made. However, over the past decade the principles underlying consistency theories have been revived in the form of connectionist models of constraint satisfaction. We then review experimental work on complex legal decision making that illustrates how constraint-satisfaction mechanisms can cause coherence shifts, thereby transforming ambiguous imputs into coherent decisions.

A constraint-satisfaction approach to clerical work

The authors present a constraint satisfaction mechanism for office systems. Describing clerical work with a consistency maintenance model, they have developed a constraint syntax and an interactive constraint satisfaction engine for clerical work. They have used constraints to rewrite an operational office system.

Neural Dynamics for Preattentive Perceptual Grouping: Linking Gestalt Laws and Cortical Synchronisation

As revealed by the Gestalt school in the first half of the century, visual perception is governed by certain simple rules which group parts into wholes in accordance to ‘laws’ like grouping by proximity, similarity, closure, symmetry, and good continuation. Although these principles can be investigated by experiment, their underlying neural computation is largely unknown. It has been speculated that synchronisations of visual cortical neurons may serve as the carrier for the observed perceptual grouping phenomenon. We present a neural network for preattentive perceptual grouping derived from neurophysiological and psychophysical findings, incorporating a relaxation phase labeling and diffusion process. The network groups visual features into perceptual entities by (de)synchronising parametric phase labels of simple neural oscillators using a constraint satisfaction mechanism. The local constraints between features, which model the Gestaltist grouping principles of proximity and good continuation, act horizontally in and vertically between feature dimensions to allow for the emergent segregation of globally salient contours in phase space, suppressing false responses generated from the edge detection stage. By applying the grouping mechanism to various contour types ranging from dotted lines to intensity edges we show that the phase-based object representation is able to account for various perceptual phenomena like the closing of small contour gaps and the perception of illusory contours. Based solely on edge responses and local interactions thereupon, the neural dynamics allows the emergent formation of globally distinguishable objects in phase space, which can be extracted by an attentional mechanism tracking the spatially modulated phase information.

Improving object-oriented user interfaces with constraints

The user interface is a crucial part of any modern computer system. Much effort is spent on its design and coding. Object-oriented (OO) user interface technology increases the productivity of interface designers and programmers. The paper describes the concepts used to build OO user interfaces, in particular the frameworks used by the Smalltalk-80 MVC user interface paradigm and the InterViews user interface toolkit for the XII window system. However, there are some shortcomings in the OO approach. To address them, constraints are introduced. Constraints are declared relationships among objects that are maintained by a constraint-satisfaction mechanism. While in OO user interfaces its components communicate via messages according to pre-established protocols, here the relationships are described declaratively with structured sets of maintained constraints and a framework developed to compose user interfaces based on different types of constraints.

A modeling system for top-down design of assembled products

The design of a mechanical product usually takes place primarily in a top-down fashion, where the designer first generates a rough, overall sketch of the product and its main components. Later, the designer refines the sketch to a detailed level while taking into account the relevant requirements posed by strength, cost, manufacturability, serviceability, and other similar considerations. Current computer-aided design (CAD) systems provide only limited support for this kind of work. For instance, they cannot deal with geometric or other information at varying levels of detail, nor do they capture explicitly geometric relationships among components intended to be joined together in an assembly. This paper describes early results of ongoing research on supporting top-down design of mechanical products and discusses the major requirements for CAD systems used for top-down design. A prototype design system is described that provides the following characteristics not usually found in ordinary CAD systems: structuring of product information in several layers, according to the stage of the design process; representation of geometric information about components at several levels of detail; and representation and maintenance of geometric relationships of components by means of a constraint-satisfaction mechanism.

Images and inference

It is frequently asked whether imagery differs in a fundamental way from other forms of knowledge representation, specifically the predicative forms employed in artificial intelligence programs. Frequently suggested distinctions are pictorial versus descriptional, and analog versus digital. This paper argues that these distinctions are not central in understanding the role of imagery in cognition, and moreover do not correctly capture the difference between visual perception and language. A distinction is proposed between the representation of images, on the one hand, and a calculus-plus-proof-procedure form of knowledge representation on the other. This distinction is not based upon differences in expressive power or form, but rather is based upon a distinction between how these two representations function, specifically how they are used to make inferences. On this view, an important functional role of imagery is to provide a non-proof-procedural method for inference, using a constraint satisfaction mechanism. Images, even the limited class of images here called diagrams, support inference in a way that is distinct from the way predicative representations support inference. This analysis offers an approach to solving the “frame problem” of cognitive science.

Constraint hierarchies

Constraints describe relations that must be maintained, and provide a useful tool for such applications as interactive simulations, algorithm animation, and graphical user interface construction. We describe a major overhaul and extension to the constraint satisfaction mechanism in ThingLab, a constraint-oriented simulation laboratory written in the Smalltalk-80 language. First, a specification is presented of constraint hierarchies . Such hierarchies include both required constraints and default constraints of differing strengths, thus adding considerable expressive power to the system. Second, an algorithm for satisfying constraint hierarchies is described. The new satisfier is substantially faster than the previous version, even though it also includes new functionality.