Constraint Satisfaction Model Research Articles

Coherence as an Alternative to Strategic Complementarity at an Entrepreneurial Firm

Organisational change processes are complex, idiosyncratic, and seemingly nonstochastic. Theories of strategic complementarity present change as the evolution of systems of mutual reinforcement among heterogeneous elements within the firm. This paper combines theories of strategic complementarity and entrepreneurial sense-making to develop an alternate heuristic of entrepreneurial adaptation as a search for coherence. Within a framework of narrative rationality, I define coherence as inference or search for the best explanation. A case study of organisational change at an entrepreneurial biotechnology firm provides the backdrop for the modeling exercise. A constraint satisfaction model reveals coherent systems of heterogeneous organizational elements. The model recapitulates organizational structuring observed at the firm. The success of the organization despite violating the primary heuristic of complementarity suggests that strategic theories of fitness must be applied with caution in entrepreneurial contexts. This paper contributes to the study of fitness generally and the specific application of fitness regimes in entrepreneurial contexts, specially when high uncertainty and resource scarcity limits strategic analysis and implementation.

On the theoretical precision and strategy selection problem of a single‐strategy approach: A comment on Glöckner, Betsch, and Schindler (2010)

AbstractAccording to the fast and frugal heuristics (FFH) program, humans make decisions by selecting from a repertoire of strategies. Glöckner, Betsch, and Schindler criticize such multi‐strategy frameworks for not explaining how people select between the different strategies. As an alternative, they propose a parallel constraint satisfaction (PCS) model that assumes a single strategy for all tasks. However, contrary to Glöckner et al.'s assertions, the FFH and other multi‐strategy frameworks have developed a number of approaches to strategy selection, tackling a difficult modeling problem that the PCS model disguises but cannot solve itself. Moreover, in contrast to the PCS model, which has not been completely spelled out, the repertoire of strategies assumed by the FFH framework is precisely defined, enabling researchers to make quantitative predictions about behavior. Copyright © 2010 John Wiley & Sons, Ltd.

Coherence shifts in probabilistic inference tasks

AbstractThe fast‐and‐frugal heuristics approach to probabilistic inference assumes that individuals often employ simple heuristics to integrate cue information that commonly function in a non‐reciprocal fashion. Specifically, the subjective validity of a certain cue remains stable during the application of a heuristic and is not changed by the presence or absence of another cue. The parallel constraint satisfaction (PCS) model, in contrast, predicts that information is processed in a reciprocal fashion. Specifically, it assumes that subjective cue validities interactively affect each other and are modified to coherently support the favored choice. Corresponding to the model's simulation, we predicted the direction and the size of such coherence shifts. Cue validities were measured before, after (Experiment 1), and during judgment (Experiments 2 and 3). Coherence shifts were found in environments involving real‐world cue knowledge (weather forecasts) and in a domain for which the application of fast‐and‐frugal heuristics has been demonstrated (city‐size tasks). The results indicate that subjective cue validities are not fixed parameters, but that they are interactively changed to form coherent representations of the task. Copyright © 2009 John Wiley & Sons, Ltd.

Physiological arousal in processing recognition information: Ignoring or integrating cognitive cues?

AbstractThe recognition heuristic (RH; Goldstein & Gigerenzer, 2002) suggests that, when applicable, probabilistic inferences are based on a noncompensatory examination of whether an object is recognized or not. The overall findings on the processes that underlie this fast and frugal heuristic are somewhat mixed, and many studies have expressed the need for considering a more compensatory integration of recognition information. Regardless of the mechanism involved, it is clear that recognition has a strong influence on choices, and this finding might be explained by the fact that recognition cues arouse affect and thus receive more attention than cognitive cues. To test this assumption, we investigated whether recognition results in a direct affective signal by measuring physiological arousal (i.e., peripheral arterial tone) in the established city-size task. We found that recognition of cities does not directly result in increased physiological arousal. Moreover, the results show that physiological arousal increased with increasing inconsistency between recognition information and additional cue information. These findings support predictions derived by a compensatory Parallel Constraint Satisfaction model rather than predictions of noncompensatory models. Additional results concerning confidence ratings, response times, and choice proportions further demonstrated that recognition information and other cognitive cues are integrated in a compensatory manner.

Complex university course timetabling

This paper summarizes the work done to solve a complex course timetabling problem at a large university and provides new insights into the overall timetabling process. The first step in the successful solution of this problem was to define a course structure model that allowed application of classical course timetabling methods. Several methods were necessary to solve the complete problem. First, support procedures were needed to detect and correct an infeasible problem where hard constraints were being violated. The resulting timetabling problem was then solved via a search for a complete assignment of times and rooms to classes, taking all hard and soft constraints into account. Methods were also developed for modifying a computed solution in response to changes introduced at a later time while having a minimal impact on existing assignments. These problems are described formally using a weighted constraint satisfaction model of the timetabling problem and solutions are proposed through two types of the algorithms: (1) generic iterative forward search with conflict-based statistics, and (2) branch and bound. Experimental results from the course timetabling system developed for Purdue University are provided. These include solutions computed by university schedulers using the system for two separate terms along with extensive experiments solving two central and six departmental problems, individually, and as a combined problem with almost 2,500 classes. The system described is currently used on all of the many varied course timetabling problems encountered each term at Purdue University.

Parallel Constraint Satisfaction in Memory-Based Decisions

Three studies sought to investigate decision strategies in memory-based decisions and to test the predictions of the parallel constraint satisfaction (PCS) model for decision making (Glöckner & Betsch, 2008). Time pressure was manipulated and the model was compared against simple heuristics (take the best and equal weight) and a weighted additive strategy. From PCS we predicted that fast intuitive decision making is based on compensatory information integration and that decision time increases and confidence decreases with increasing inconsistency in the decision task. In line with these predictions we observed a predominant usage of compensatory strategies under all time-pressure conditions and even with decision times as short as 1.7 s. For a substantial number of participants, choices and decision times were best explained by PCS, but there was also evidence for use of simple heuristics. The time-pressure manipulation did not significantly affect decision strategies. Overall, the results highlight intuitive, automatic processes in decision making and support the idea that human information-processing capabilities are less severely bounded than often assumed.

Parallel Constraint Satisfaction in Memory-Based Decisions

Three studies sought to investigate decision strategies in memory-based decisions and to test the predictions of the parallel constraint satisfaction (PCS) model for decision making (Glockner & Betsch, 2008). Time pressure was manipulated and the model was compared against simple heuristics (take the best and equal weight) and a weighted additive strategy. From PCS we predicted that fast intuitive decision making is based on compensatory information integration and that decision time increases with increasing inconsistency in the decision task. In line with these predictions we observed a predominant usage of compensatory strategies under all time pressure conditions and even with decision times as short as 1.7 seconds. For a substantial number of participants, choices and decision times were best explained by PCS, but there was also evidence for use of simple heuristics. The time pressure manipulation did not significantly affect decision strategies. Overall, the results highlight intuitive, automatic processes in decision making and support the idea that human information-processing capabilities are less severely bounded than often assumed.

Exploring the dynamics of the appraisal–emotion relationship: A constraint satisfaction model of the appraisal process

This paper presents a computational model of emotions that is based in an appraisal theoretical framework. The model explores the dynamics of the appraisal–emotion relationship using parallel constraint satisfaction. It proposes belief coherence, desire coherence and belief–desire coherence as basic principles and specifies how these principles can be realised in a parallel constraint satisfaction system. The model shows that the very same mechanisms that account for the formation of coherence or consistency are also pivotal for the emergence and alteration of emotional states and for the dynamics of the cognition–emotion relationship. Concrete simulation examples show how discrete emotions such as anger, pride, sadness, shame, surprise, relief and disappointment emerge out of these principles.

Imaging the past: Neural activation in frontal and temporal regions during regular and irregular past-tense processing

This article presents fMRI evidence bearing on dual-mechanism versus connectionist theories of inflectional morphology. Ten participants were scanned at 4 Tesla as they covertly generated the past tenses of real and nonce (nonword) verbs presented auditorily. Regular past tenses (e.g., walked, wugged) and irregular past tenses (e.g., took, slept) produced similar patterns of activation in the posterior temporal lobe in both hemispheres. In contrast, there was greater activation in left and right inferior frontal gyrus for regular past tenses than for irregular past tenses. Similar previous results have been taken as evidence for the dual-mechanism theory of the past tense (Pinker & Ullman, 2002). However, additional analyses indicated that irregulars that were phonologically similar to regulars (e.g., slept, fled, sold) produced the same level of activation as did regulars, and significantly more activation than did irregulars that were not phonologically similar to regulars (e.g., took, gave). Thus, activation patterns were predicted by phonological characteristics of the past tense rather than by the rule-governed versus exception distinction that is central to the dual-mechanism framework. The results are consistent with a constraint satisfaction model in which phonological, semantic, and other probabilistic constraints jointly determine the past tense, with different degrees of involvement for different verbs.

Long-term effects of vaccination on attentional performance

To investigate the possible influence of stimulation of the immune system on cognitive tasks, healthy volunteers were vaccinated against hepatitis B and tested over a 6 month-period in a simple reaction times and the Stroop task. In general, the “Stroop effect” demonstrates that both the name and meaning of a word are automatically processed even when voluntary attention is trying hard not to process them. Unlike placebo group, vaccinated subjects showed a persistent lack of the classical Stroop effect. These findings may be explained by a constraint satisfaction model of the Stroop task, assuming a selective weakening of the connection matrix, and suggest that immune–cognitive effects may occur, besides the well known immune–cognitive influences like those elicited by emotional stress.

Empirical Evaluation of Traffic Performance of Inter-Agent Communication Systems with Mobile Agents

In this paper we study the basic characteristics of traffic performance of agent communication systems, focusing upon the mobility of agents. First, we will briefly introduce several application models in terms of when, where and for what purposes the agent should be moved. Then we will focus on the model in which the mobility is used for trying to reduce the total communication cost among the agents and develop a simple model on top of some kind of distributed constraint satisfaction model. Finally, we will show the empirical results obtained from the simulation and discuss how the mobility could affect the overall performance of this type of systems.

A constraint satisfaction model for recognition of stop consonant-vowel (SCV) utterances

We propose a model for recognition of utterances of consonant-vowel (CV) units. The acoustic-phonetic knowledge of the CV classes is incorporated in the form of constraints of a constraint satisfaction model. The model combines evidence from multiple classifiers. The significant feature of this model is that discrimination of the CV units could be enhanced by a combination of even weak evidence derived from the features. The evidence is obtained from multilayer feedforward neural networks trained for subgroups of CV classes. The evidence is enhanced using a set of feedback subnetworks in the constraint satisfaction model. The weights for the connections in the feedback subnetworks are derived using acoustic-phonetic knowledge and the performance statistics of the trained networks. The performance of the proposed model is demonstrated for recognition of utterances of a large number (80) of stop consonant-vowel units for the Indian language Hindi.

Binary vs. non-binary constraints

There are two well known transformations from non-binary constraints to binary constraints applicable to constraint satisfaction problems (CSPs) with finite domains: the dual transformation and the hidden (variable) transformation. We perform a detailed formal comparison of these two transformations. Our comparison focuses on two backtracking algorithms that maintain a local consistency property at each node in their search tree: the forward checking and maintaining arc consistency algorithms. We first compare local consistency techniques such as arc consistency in terms of their inferential power when they are applied to the original (non-binary) formulation and to each of its binary transformations. For example, we prove that enforcing arc consistency on the original formulation is equivalent to enforcing it on the hidden transformation. We then extend these results to the two backtracking algorithms. We are able to give either a theoretical bound on how much one formulation is better than another, or examples that show such a bound does not exist. For example, we prove that the performance of the forward checking algorithm applied to the hidden transformation of a problem is within a polynomial bound of the performance of the same algorithm applied to the dual transformation of the problem. Our results can be used to help decide if applying one of these transformations to all (or part) of a constraint satisfaction model would be beneficial.

Shifting Standards and Contextual Variation in Stereotyping

This chapter provides an overview of some 10 years of research on the “Shifting Standards Model” (Biernat, Manis, & Nelson, 1991). This model suggests that stereotypes lead perceivers to evaluate individual group members relative to within-category standards. One result of this process is that subjective evaluations (e.g., judgments on semantic-differential scales) may “mask” the operation of stereotypes. For example, a man and a woman may both be described as equally “competent”, even when more “objective” evaluations reveal substantial stereotyping effects (e.g., the man is assumed to score higher on standardized tests of competency). This review focuses on the role of context in moderating the tendency to shift judgment standards, and provides a critical comparison of the shifting standards model with two other theories emphasizing contextual variation in stereotyping, Social Identity/Self-Categorization Theory (Tajfel, 1972; Turner, 1982; Turner, Hogg, Oakes, Reicher, & Wetherell, 1987), and the Parallel Constraint Satisfaction Model of impression formation (Kunda & Thagard, 1996).

Timetable planning using the constraint-based reasoning

College timetabling is a combinatoric and dynamic problem. In order to solve this problem, the approach must be efficient, flexible, portable, and adaptable. This paper describes a solution procedure based on a constraint-based reasoning technique implemented in an object-oriented approach. The problem is formulated as a constraint satisfaction model and it is then solved using the proposed algorithm. The algorithm is tested using real data from one of the colleges offering professional courses. The results show that a 18-weeks timetable for 1673 subject sections, 10 rooms, 21 lecturers can be solved in less than 33 minutes as compared to several weeks if it is to be solved manually. Since it is implemented using the object-oriented approach, the proposed system can also be modified and easily adapted to support changes. Scope and purpose Timetable planning is an activity of assigning subjects to time and space such that all constraints are satisfied. It can be categorized into several types and the most common types are academic (in universities, colleges, and schools), airline, and nurse timetablings. Constraint-based reasoning is a problem-solving technique that combines logic programming and constraint-solving technique based on an arc-consistency algorithm. It has been used to solve constraint satisfaction problems. The purpose of the paper is to present the modeling process of the college timetabling as a constraint satisfaction problem. The model is then solved using the constraint-based reasoning approach.

Free Choice and Cognitive Dissonance Revisited: Choosing “Lesser Evils” Versus “Greater Goods”

Traditional dissonance theory predicts a spreading apart of chosen and rejected alternatives following a decision. More recent constraint satisfaction models of this classic free-choice paradigm suggest that these effects may vary with the overall attractiveness of the choice options. This prediction was tested with 13-year-olds choosing among posters. As in prior computer simulations, a difficult choice between generally less desirable alternatives produced a large increase in participants’ evaluations of the chosen alternative, whereas a difficult choice between generally more desirable alternatives produced a large decrease in evaluations of the rejected alternative. The results were discussed in terms of the relative amounts of dissonance created in the various conditions. The utility of the consonance constraint satisfaction model that generated these novel predictions was stressed.

Supervised texture classification using a probabilistic neural network and constraint satisfaction model

In this paper, the texture classification problem is projected as a constraint satisfaction problem. The focus is on the use of a probabilistic neural network (PNN) for representing the distribution of feature vectors of each texture class in order to generate a feature-label interaction constraint. This distribution of features for each class is assumed as a Gaussian mixture model. The feature-label interactions and a set of label-label interactions are represented on a constraint satisfaction neural network. A stochastic relaxation strategy is used to obtain an optimal classification of textures in an image. The advantage of this approach is that all classes in an image are determined simultaneously, similar to human perception of textures in an image.

Program Understanding as Constraint Satisfaction: Representation and Reasoning Techniques

The process of understanding a source code in a high-level programming language involves complex computation. Given a piece of legacy code and a library of program plan templates, understanding the code corresponds to building mappings from parts of the source code to particular program plans. These mappings could be used to assist an expert in reverse engineering legacy code, to facilitate software reuse, or to assist in the translation of the source into another programming language. In this paper we present a model of program understanding using constraint satisfaction. Within this model we intelligently compose a partial global picture of the source program code by transforming knowledge about the problem domain and the program itself into sets of constraints. We then systematically study different search algorithms and empirically evaluate their performance. One advantage of the constraint satisfaction model is its generality; many previous attempts in program understanding could now be cast under the same spectrum of heuristics, and thus be readily compared. Another advantage is the improvement in search efficiency using various heuristic techniques in constraint satisfaction.

University timetabling by constraint-based reasoning: A case study

This paper presents a case-study which applies constraint-based reasoning to university timetable planning. The timetabling problem is formulated as a constraint satisfaction model and this model is solved using constrained-directed search algorithms with built-in forward checking and constraint propagation. The model and algorithms were tested with real data containing 536 lessons to be scheduled into 45 timeslots and 21 rooms. The solution to the problem was obtained with minimal computing effort and processing time. This study showed that modelling and remodelling could be carried out easily through a proposed parameterised model formulation. The proposed approach has also successfully maximised room utilisation and minimised the number of timeslots required to deliver all the lectures. This finding may facilitate the widespread implementation of automated timetabling systems to larger scale problems and a wider variety of application domains.

A framework of constraint-based modeling for cooperative decision systems

Multi-agent technology has emerged as a promising discipline for modeling distributed information system applications. One of such applications is the modeling of cooperative decision systems. The knowledge used in such systems is typically uncertain, heuristic, and temporally changing. In this paper, we propose a framework to model cooperative decision systems. In the framework, a mechanism of situation representation is used to model temporally changing problem-solving states and interactions within the environment. A heuristic constraint satisfaction model is exploited as a means of decision-making with incomplete information. A cooperation protocol based on the situation mechanism and the heuristic constraint model is designed.