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Lanny Fields - One of the best experts on this subject based on the ideXlab platform.
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Equivalence Class formation when responding is separated from sample and comparison stimuli working memory priming and sorting
Journal of the Experimental Analysis of Behavior, 2021Co-Authors: Lanny Fields, Erica Doran, John J FoxeAbstract:The experiment determined whether Equivalence Class formation required overlap of comparison stimuli and responding. Each trial contained a sample first, a single, nonoverlapping comparison second, and a nonoverlapping response-window (RW) third, during which the participant made one of two responses (2R). All 11 participants formed two 3-member ABC Equivalence Classes using these "trace-stimulus-pairing two-response with response window" (TSP-2R-RW) trials. After adding a fourth stimulus (D) by CD training, ABCD tests showed immediate expansion to 4-member ABCD Classes. When 4-member probes (AD, DA, BD, DB, CD, DC) were administered without 3-member probes, many participants showed decrements in Class-indicative responding that then resurged to mastery with test repetition. Thus, 3-member probes enhanced Class expansion. Class formation occurred for all participants when responding was temporally dissociated from the comparisons. In a matched, contemporaneously published experiment, where responding occurred during comparisons, only 54% of participants formed the Classes. Thus, the comparison-response-separation nearly doubled Class formation. Additionally, a special post-Class-formation sorting test documented the emergence of two explicit Equivalence Classes. Finally, we noted a 1:1 correspondence for TSP-2R-RW and priming trials. Since priming measures neural substrates of Equivalence Classes, TSP-2R-RW trials should do the same.
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Yield as an Essential Measure of Equivalence Class Formation, Other Measures, and New Determinants
The Psychological Record, 2020Co-Authors: Lanny Fields, Erik Arntzen, Erica DoranAbstract:“Yield,” the percentage of participants in a group who form a set of Equivalence Classes, has been used very broadly to identify the effect of different training protocols on Class formation and expansion, identify variables that enhance the immediate emergence of these Classes, and characterize the differential relatedness of Class members. In addition, yield is now being used to document the formation of educationally relevant Equivalence Classes. To further understand the value of using yield, we considered six possible criticisms of its use to study Equivalence Classes. Upon analysis, each criticism was supported; instead, each disclosed a nonyield factor that could play a critical role in the measurement of Class formation but has not yet been explored experimentally. Finally, yield cannot be replaced with trial-based measures of responding or vice versa; rather, both types of measures are needed to obtain a comprehensive understanding of Equivalence Class formation.
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Training Modality and Equivalence Class Formation under the Simultaneous Protocol: A Test of Stimulus Control Topography Coherence Theory
The Psychological Record, 2020Co-Authors: Lanny Fields, Debra PaoneAbstract:This experiment explored how training modality influenced the formation of three-node, five-member Equivalence Classes during the simultaneous protocol by 23 college students. The baseline relations were established in one of three ways: concurrently (CONC; i.e., all together), serially (SER; i.e., one after another)—both on a trial and error basis—or serially and “errorlessly” by use of a constructed response matching to sample procedure (CRMTS). After training, Class formation was assessed with test blocks that contained all baseline relations trials and probe trials for symmetry, transitivity, and Equivalence. Error percentages during the acquisition of the baseline relations was highest during concurrent training, lower during serial training, and lowest during constructed response training. Yet, a similar percentage of participants formed Classes in each training condition. Thus, the likelihood of Equivalence Class formation under these variants of the simultaneous protocol was not influenced by training modality or prevalence of errors during acquisition. In addition, only some of the transient nonClass-indicative stimulus control topographies that emerged during training resurged during testing. These results challenge predictions regarding Class formation posited by stimulus control topography coherence theory.
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Meaningful Stimuli and the Enhancement of Equivalence Class Formation
Behavior Analyst, 2017Co-Authors: Lanny Fields, Erik ArntzenAbstract:Stimulus meaningfulness has been defined by its hedonic valence, denotative (definitional) and connotative (evaluative) properties, and its influence on forming categories called Equivalence Classes. Positive or negative hedonic value of a meaningful stimulus transfers to the other members of an Equivalence Class that contains such a stimulus, and also influences likelihood of Class formation. The denotative and connotative properties of meaningful stimuli are instantiated by the responses they produced (simple discriminative functions) and by the selection of other related words (conditional discriminative functions). If a meaningless cue acquires one such stimulus control function, and is included in a set of otherwise meaningless stimuli, its inclusion enhances the formation of an Equivalence Class. These results suggest ways to enhance Equivalence Class formation in applied settings. When degree of enhancement matches that produced by the inclusion of a meaningful stimulus in a Class, Class enhancement can be accounted for by the stimulus control functions it serves, as well as its hedonic, denotative, and connotative properties. We also linked Equivalence Class formation and meaningfulness to semantic networks, relational frame theory, verbal behavior, and naming.
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Training order and structural location of meaningful stimuli: Effects on Equivalence Class formation
Learning & Behavior, 2015Co-Authors: Richard K Nartey, Erik Arntzen, Lanny FieldsAbstract:In the present study, Equivalence Class formation was influenced by the temporal point of inclusion of a meaningful stimulus when baseline relations were serially or sequentially trained, and much less so by the location of the meaningful stimulus in the nodal structure of the Class. In Experiment 1, participants attempted to form three 3-node, 5-member Classes (A→B→C→D→E) under the simultaneous protocol. After serially training the baseline relations AB, BC, CD, and DE, in that order, the emergence of all emergent relations was tested concurrently. In the A-as-PIC condition, A was meaningful stimulus and B to E were meaningless stimulus, and 60 % of the participants formed Classes. In addition, Classes were formed by 40 %, 70 %, 40 %, and 20 % of the participants in the B-as-PIC, C-as-PIC, D-as-PIC, and E-as-PIC groups, respectively. Thus, the likelihood of Class formation could have been influenced by the location of a meaningful stimulus in the Class structure and/or by its order of introduction during training. In Experiment 2, we controlled for any effect of order of introduction by the concurrent training of all of the baseline relations. Regardless of the location of the meaningful stimulus, 0–20 % of participants formed Classes. Thus, the temporal order of introducing a meaningful stimulus was the primary modulator of the Class-enhancing property of meaningful stimuli, and not the location of the meaningful stimulus in the Class structure.
Erik Arntzen - One of the best experts on this subject based on the ideXlab platform.
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Yield as an Essential Measure of Equivalence Class Formation, Other Measures, and New Determinants
The Psychological Record, 2020Co-Authors: Lanny Fields, Erik Arntzen, Erica DoranAbstract:“Yield,” the percentage of participants in a group who form a set of Equivalence Classes, has been used very broadly to identify the effect of different training protocols on Class formation and expansion, identify variables that enhance the immediate emergence of these Classes, and characterize the differential relatedness of Class members. In addition, yield is now being used to document the formation of educationally relevant Equivalence Classes. To further understand the value of using yield, we considered six possible criticisms of its use to study Equivalence Classes. Upon analysis, each criticism was supported; instead, each disclosed a nonyield factor that could play a critical role in the measurement of Class formation but has not yet been explored experimentally. Finally, yield cannot be replaced with trial-based measures of responding or vice versa; rather, both types of measures are needed to obtain a comprehensive understanding of Equivalence Class formation.
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Equivalence Class Formation and the N400: Methodological Issues
The Psychological Record, 2019Co-Authors: Guro Granerud-dunvoll, Erik Arntzen, Torbjørn Elvsåshagen, Christoffer Hatlestad-hall, Eva MaltAbstract:The electroencephalogram (EEG)-based N400 component is often described as an index of a semantic relation. Recent studies suggested that the N400 component can also be used as an electrophysiological measure of Equivalence Class formation, yet more research is needed to clarify the effects of experimental conditions on the N400 response. In Experiment 1 of the present study, the participants were trained on six conditional discriminations and tested for the formation of three 3-member Classes. If they formed Equivalence Classes with half of the possible emerged relations, the participants were given a priming test with the other half. Related and unrelated stimulus pairs were presented, and the participant had to decide whether the stimuli were related or not. The results showed that a nonsignificant N400 response was observed after unrelated stimulus pairs were presented but not when related stimulus pairs were presented. The strength of the N400 response weakened over the number of stimuli presentations. In Experiment 2, we examined whether changes to the methodology of Experiment 1 would produce stronger N400 responses. The participants also underwent a word priming procedure, which has been shown to produce robust N400 responses. We found more robust N400 responses in Experiment 2 than in Experiment 1, and the N400 response was larger in transitivity/Equivalence relations than in symmetry relations. There was also a significant relation effect in the word priming procedure. Together, these findings support the notion that the N400 component can be used as an electrophysiological measure of Equivalence Class formation and illustrate how experimental conditions can influence the N400 response.
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Equivalence Class formation as a function of preliminary training with pictorial stimuli
Journal of the Experimental Analysis of Behavior, 2018Co-Authors: Erik Arntzen, Richard K NarteyAbstract:The present experiment investigated the effects of preliminary training with pictorial stimuli on the subsequent formation of three 5-member Equivalence Classes (A➔B➔C➔D➔E) in 84 university students assigned to seven groups of 12. In the Abstract (ABS) group, all stimuli were abstract shapes. In the Picture (PIC) group, the C stimuli were pictures, and the remaining stimuli were the same abstract shapes as in the ABS group. For the remaining five groups, all stimuli were the same abstract shapes as in the ABS group. However, across groups, preliminary training involved either the establishment of conditional relations with simultaneous (SMTS) or delayed (DMTS) matching-to-sample with 0 s, 3 s, 6 s, or 9 s between the abstract C stimuli and the meaningful pictures. For the ABS and the PIC groups, 16.7% and 83.3% of participants formed Classes, respectively. Preliminary training with SMTS and DMTS with 0 s, 3 s, and 6 s produced a linear increase in the likelihood of Equivalence Class formation, 41.7%, 50%, and 75%, respectively. Increasing the duration of delay further from 6 s to 9 s produced a substantial decline, 50%. This experiment extends knowledge about how including meaningful pictures enhances Equivalence Class formation.
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Meaningful Stimuli and the Enhancement of Equivalence Class Formation
Behavior Analyst, 2017Co-Authors: Lanny Fields, Erik ArntzenAbstract:Stimulus meaningfulness has been defined by its hedonic valence, denotative (definitional) and connotative (evaluative) properties, and its influence on forming categories called Equivalence Classes. Positive or negative hedonic value of a meaningful stimulus transfers to the other members of an Equivalence Class that contains such a stimulus, and also influences likelihood of Class formation. The denotative and connotative properties of meaningful stimuli are instantiated by the responses they produced (simple discriminative functions) and by the selection of other related words (conditional discriminative functions). If a meaningless cue acquires one such stimulus control function, and is included in a set of otherwise meaningless stimuli, its inclusion enhances the formation of an Equivalence Class. These results suggest ways to enhance Equivalence Class formation in applied settings. When degree of enhancement matches that produced by the inclusion of a meaningful stimulus in a Class, Class enhancement can be accounted for by the stimulus control functions it serves, as well as its hedonic, denotative, and connotative properties. We also linked Equivalence Class formation and meaningfulness to semantic networks, relational frame theory, verbal behavior, and naming.
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Effects of Meaningful Stimuli Contained in Different Numbers of Classes on Equivalence Class Formation
The Psychological Record, 2017Co-Authors: Justice Mensah, Erik ArntzenAbstract:Previous experiments have investigated the function of using pictures or meaningful stimuli on Equivalence Class formation. For example, when attempting to form three 5-member Classes (A→B→C→D→E), findings have shown that pictures used as C stimuli have increased the probability of producing Equivalence Class formation relative to when all stimuli in the stimulus set are abstract. The present experiment extends the literature by examining whether the formation of Equivalence Classes varies as a function of having three (C1, C2, and C3), two (C1 and C2), or one (C1) stimulus as a picture in a set of abstract stimuli. Hence, 60 participants were randomly assigned to 4 different experimental groups: 0-picture group or abstract group (ABS), 1-picture group (1PIC), 2-pictures group (2PIC), and 3-pictures group (3PIC). In addition, we had a reference group with abstract shapes only. The findings from the present experiment showed that 2 of 15 participants in the ABS formed Classes. Also, two of 15 participants in the 1PIC formed Classes, 8 of 15 participants in the 2PIC formed Equivalence Classes, and 12 of 15 members in the 3PIC formed Classes. The statistical analysis supported the notion that Equivalence Class formation is a function of the number of pictures in a potential Equivalence Class.
Jan Peleska - One of the best experts on this subject based on the ideXlab platform.
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Experimental evaluation of a novel Equivalence Class partition testing strategy
Software & Systems Modeling, 2019Co-Authors: Felix Hubner, Wenling Huang, Jan PeleskaAbstract:In this paper, a complete model-based Equivalence Class testing strategy recently developed by the authors is experimentally evaluated. This black-box strategy applies to deterministic systems with infinite input domains and finite internal state and output domains. It is complete with respect to a given fault model. This means that conforming behaviours will never be rejected, and all non-conforming behaviours inside a given fault domain will be uncovered. We investigate the question how this strategy performs for systems under test whose behaviours lie outside the fault domain. Furthermore, a strategy extension is presented, that is based on randomised data selection from input Equivalence Classes. While this extension is still complete with respect to the given fault domain, it also promises a higher test strength when applied against members outside this domain. This is confirmed by an experimental evaluation that compares mutation coverage achieved by the original and the extended strategy with the coverage obtained by random testing. For mutation generation, not only typical software errors, but also critical HW/SW integration errors are considered. The latter can be caused by mismatches between hardware and software design, even in the presence of totally correct software.
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Effective Infinite-State Model Checking by Input Equivalence Class Partitioning
2017Co-Authors: Niklas Krafczyk, Jan PeleskaAbstract:In this paper, it is shown how a complete input Equivalence Class testing strategy developed by the second author can be effectively used for infinite-state model checking of system models with infinite input domains but finitely many internal state values and finite output domains. This Class of systems occurs frequently in the safety-critical domain, where controllers may input conceptually infinite analogue data, but make a finite number of control decisions based on inputs and current internal state. A variant of Kripke Structures is well-suited to provide a behavioural model for this system Class. It is shown how the known construction of specific input Equivalence Classes can be used to abstract the infinite input domain of the reference model into finitely many Classes. Then quick checks can be made on the implementation model showing that the implementation is not I/O-equivalent to the reference model if its abstraction to observable minimal finite state machines has a different number of states or a different input partitioning as the reference model. Only if these properties are consistent with the reference model, a detailed Equivalence check between the abstracted models needs to be performed. The complete test suites obtained as a by-product of the checking procedure can be used to establish counter examples showing the non-conformity between implementation model and reference model. Using various sample models, it is shown that this approach outperforms model checkers that do not possess this Equivalence Class generation capability.
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complete model based Equivalence Class testing for nondeterministic systems
Formal Aspects of Computing, 2017Co-Authors: Wenling Huang, Jan PeleskaAbstract:The main objective of this article is to present a complete finite black-box testing theory for non-deterministic Kripke structures with possibly infinite input domains, but finite domains for internal state variables and outputs. To this end, an abstraction from Kripke structures of this sub-domain to finite state machines is developed. It is shown that every complete black-box testing theory for (deterministic or nondeterministic) finite state machines in the range of this abstraction induces a complete black-box input Equivalence Class partition testing (IECPT) theory for the Kripke structures under consideration. Additionally, it is shown that each of these IECPT theories can be combined with random testing, such that a random value is selected from an input Equivalence Class, whenever a representative from this Class is required in a test step. Experiments have shown that this combination increases the test strength of Equivalence Class tests for systems under test (SUT) outside the fault domain, while we show here that this randomisation preserves the completeness property for SUT inside the domain. The investigations lead to several complete IECPT strategies which, to our best knowledge, were not known before for this sub-domain of Kripke structures. The elaboration and presentation of results is performed on a semantic level, so that the testing theories under consideration can be applied to models presented in any concrete formalism, whose behaviour is reflected by a member of our semantic category.
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Complete model-based Equivalence Class testing
International Journal on Software Tools for Technology Transfer, 2016Co-Authors: Wenling Huang, Jan PeleskaAbstract:In this article, we present a model-based black-box Equivalence partition testing strategy, together with a formal proof of its completeness properties. The results apply to reactive systems with large, possibly infinite input data types and finite internal and output data ranges that may be enumerated with acceptable effort. The investigation is performed on a semantic level and applies to all concrete test models whose behavioural semantics can be encoded as a variant of state transition systems. Test suite construction is performed in relation to a given fault model $$\mathcal{F}$$ F for which a finite black-box test suite can be constructed which is complete with respect to $$\mathcal{F}$$ F . It is shown how the test suite generation can be effectively implemented by model-based testing tools, using propositional representations of behavioural model semantics and constraint solvers. A SysML model of the ceiling speed monitoring function of the European Train Control System is presented as a case study, to explain theory application to a concrete modelling formalism.
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complete model based Equivalence Class testing for the etcs ceiling speed monitor
International Conference on Formal Engineering Methods, 2014Co-Authors: Cecile Braunstein, Wenling Huang, Jan Peleska, Anne Elisabeth Haxthausen, Felix Hubner, Uwe Schulze, Linh Vu HongAbstract:In this paper we present a new test model written in SysML and an associated blackbox test suite for the Ceiling Speed Monitor (CSM) of the European Train Control System (ETCS). The model is publicly available and intended to serve as a novel benchmark for investigating new testing theories and comparing the capabilities of model-based test automation tools. The CSM application inputs velocity values from a domain which could not be completely enumerated for test purposes with reasonable effort. We therefore apply a novel method for Equivalence Class testing that – despite the conceptually infinite cardinality of the input domains – is capable to produce finite test suites that are complete (i.e. sound and exhaustive) for a given fault model. In this paper, an overview of the model and the Equivalence Class testing strategy is given, and tool-based evaluation results are presented. For the technical details we refer to the published model and a technical report that is also available on the same website.
Deby Cortés - One of the best experts on this subject based on the ideXlab platform.
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Relation between Exclusion and Stimulus Equivalence Class Formation in Auditory-visual and Visual-visual Matching in Preschoolers
International Journal of Comparative Psychology, 2017Co-Authors: Elberto Antonio Plazas, Deby CortésAbstract:Author(s): Plazas, Elberto Antonio; Cortes, Deby | Abstract: The hypothesis that exclusion performance is a prerequisite for the stimulus Equivalence Class formation was assessed in preschoolers of about 5 years of age. In Experiment 1, two groups of children were trained in a set of conditional discriminations in a two-choice matching to sample format, Group 1 in an auditory-visual modality baseline, and Group 2 in a visual-visual modality baseline. Exclusion test trials included an undefined (not previously related) comparison stimulus, and a defined (i.e., related in the baseline) comparison stimulus, in the presence of an undefined sample stimulus. Selection of the undefined comparison was recorded as a correct response. Stimulus Equivalence Class formation was assessed by way of symmetry and transitivity test trials. Experiment 2 replicated the design of the first experiment, with the difference that exclusion was assessed independently and with a different baseline from symmetry and transitivity. Exclusion scores were higher for the auditory-visual groups than the visual-visual groups. In both modalities symmetry scores were superior to those in transitivity. Symmetry showed independent from the exclusion performance, but transitivity was presumably dependent from it in the auditory-visual modality.
Jie Zhao - One of the best experts on this subject based on the ideXlab platform.
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nec a nested Equivalence Class based dependency calculation approach for fast feature selection using rough set theory
Information Sciences, 2020Co-Authors: Jie Zhao, Jiaming Liang, Zhenning Dong, Deyu Tang, Zhen LiuAbstract:Abstract Feature selection plays an important role in data mining and machine learning tasks. As one of the most effective methods for feature selection, rough set theory provides a systematic theoretical framework for consistency-based feature selection, in which positive region-based dependency calculation is the most important step. However, it is time-consuming, and although many improved algorithms have been proposed, they are still computationally time-consuming. Therefore, to overcome this shortcoming, in this study, a nested Equivalence Class (NEC) approach is introduced to calculate dependency. The proposed method starts from the finest partition of the universe, and then extracts and uses the known knowledge of reducts in a decision table to construct an NEC. The proposed method not only simplifies dependency calculation but also reduces the universe correspondingly, in most cases. Using the proposed NEC-based approach, a number of representative heuristic- and swarm intelligence-based feature selection algorithms that apply rough set theory were enhanced. Note that the feature subset selected by each modified algorithm and that selected by the original algorithm were the same. Experiments conducted using 33 datasets from the UCI repository and KDD Cup competition, which included large-scale and high-dimensional datasets, demonstrated the efficiency and effectiveness of the proposed method.
