Advanced modelling of complex processes by rule based networks

Abstract We introduce the concept of Semantic Neutral Drift (SND) for genetic programming (GP), where we exploit equivalence laws to design semantics preserving mutations guaranteed to preserve individuals’ fitness scores. A number of digital circuit benchmark problems have been implemented with rule-based graph programs and empirically evaluated, demonstrating quantitative improvements in evolutionary performance. Analysis reveals that the benefits of the designed SND reside in more complex processes than simple growth of individuals, and that there are circumstances where it is beneficial to choose otherwise detrimental parameters for a GP system if that facilitates the inclusion of SND.

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Within-trial variability improves rule-based, not information-integration, category learning

10.31234/osf.io/h9ewf ◽

2018 ◽

Author(s):

Casey L Roark ◽

Lori L. Holt

Keyword(s):

Category Learning ◽

Information Integration ◽

Rule Based ◽

Acoustic Environment ◽

Complex Processes ◽

Tightly Coupled ◽

Single Category ◽

Category Variability ◽

Learning Trials ◽

Slow Learning

Categorization is a critical component of cognition and contributes to many complex processes, including speech perception. High variability within the environment is thought to initially slow learning while increasing the ability to generalize to novel exemplars. However, little is understood about the mechanisms driving this benefit of variability. The current study investigates the effect of pairing within-category variability with response and feedback within single category-learning trials. Participants who learned categories defined by boundaries orthogonal to the category dimensions—rule-based categories—had superior learning and were better able to generalize to novel exemplars when they were trained with within-trial variability compared to when only a single exemplar was presented on each trial. In contrast, participants who learned categories defined by boundaries involving reliance on both category input dimensions—information-integration categories—showed no enhancement of learning from within-category variability. This draws a distinction between overall variability in the acoustic environment and variability more tightly coupled with response and feedback. The influence of variability as experienced within a single trial differs substantially depending on the nature of the category learning challenge. The results have implications for learning speech categories and for further understanding the mechanisms that contribute to auditory category learning.

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Using Conventional Articulation Tests With Highly Unintelligible Children

Language Speech and Hearing Services in Schools ◽

10.1044/0161-1461.2301.52 ◽

1992 ◽

Vol 23 (1) ◽

pp. 52-60 ◽

Cited By ~ 1

Author(s):

Pamela G. Garn-Nunn ◽

Vicki Martin

Keyword(s):

Test Results ◽

Phonological Processes ◽

Rule Based ◽

Severity Level ◽

Error Sensitivity ◽

Conventional Tests ◽

Severity Levels ◽

Conventional Test ◽

Impaired Children

This study explored whether or not standard administration and scoring of conventional articulation tests accurately identified children as phonologically disordered and whether or not information from these tests established severity level and programming needs. Results of standard scoring procedures from the Assessment of Phonological Processes-Revised, the Goldman-Fristoe Test of Articulation, the Photo Articulation Test, and the Weiss Comprehensive Articulation Test were compared for 20 phonologically impaired children. All tests identified the children as phonologically delayed/disordered, but the conventional tests failed to clearly and consistently differentiate varying severity levels. Conventional test results also showed limitations in error sensitivity, ease of computation for scoring procedures, and implications for remediation programming. The use of some type of rule-based analysis for phonologically impaired children is highly recommended.

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Haunted by a Doppelgänger

Experimental Psychology (formerly Zeitschrift für Experimentelle Psychologie) ◽

10.1027/1618-3169/a000221 ◽

2014 ◽

Vol 61 (1) ◽

pp. 12-22 ◽

Cited By ~ 11

Author(s):

Bettina von Helversen ◽

Stefan M. Herzog ◽

Jörg Rieskamp

Keyword(s):

Relevant Information ◽

Psychological Research ◽

Decision Makers ◽

Human Judgment ◽

Rule Based ◽

New Employees ◽

High Performing ◽

Facial Similarity ◽

Similarity Effect ◽

Judgment Strategy

Judging other people is a common and important task. Every day professionals make decisions that affect the lives of other people when they diagnose medical conditions, grant parole, or hire new employees. To prevent discrimination, professional standards require that decision makers render accurate and unbiased judgments solely based on relevant information. Facial similarity to previously encountered persons can be a potential source of bias. Psychological research suggests that people only rely on similarity-based judgment strategies if the provided information does not allow them to make accurate rule-based judgments. Our study shows, however, that facial similarity to previously encountered persons influences judgment even in situations in which relevant information is available for making accurate rule-based judgments and where similarity is irrelevant for the task and relying on similarity is detrimental. In two experiments in an employment context we show that applicants who looked similar to high-performing former employees were judged as more suitable than applicants who looked similar to low-performing former employees. This similarity effect was found despite the fact that the participants used the relevant résumé information about the applicants by following a rule-based judgment strategy. These findings suggest that similarity-based and rule-based processes simultaneously underlie human judgment.

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