Vibratory roughness perception occurs when people feel a surface with a rigid probe. Accordingly, perceived roughness should reflect probe and surface geometry, exploratory speed, and force. Experiments 1 and 2 compared magnitude estimation of roughness with the bare finger and two types of probes, one designed to eliminate force moments, under the subject’s active control. Experiments 3 and 4 varied speed under passive control. Log magnitude was consistently a quadratic function of log spacing between elements in the surface. The location of the function’s peak was related to the drop point— that is, the spacing at which the probe can just drop between elements—which is affected by probe tip diameter, element height, and speed. Other parameters of the quadratic were affected by probe type and speed.

Over more than a half century of experience in research on learning, memory, and decision, I have come to believe that the most substantial and enduring advances have not been in the accumulation of empirical facts or the construction of models, but in the production of fruitful interactions between models and experimental research. Most experimental facts require continual reinterpretation and most models drop by the wayside like autumn leaves, but the results of interactions between models and experiments constitute most of our generalizable knowledge. Success in the interactive research effort depends not only on clearly formulated models and well-conducted experiments, but, just as importantly, on sound interpretations of the results of applying the models to the experiments. This interpretive phase of the effort is in some respects the most difficult, and I take as my main task in this article an account of some of the issues that have to be resolved and some of the traps that have to be avoided in order for the process to run to a successful conclusion. As a preliminary, I turn to a review of the basic concept of applying a model to data as it has evolved since its first rudimentary instantiation in the literature of memory and decision more than a century ago. Applying Models to Experiments Details of techniques for fitting curves, or, more broadly, formal models, whether mathematical or computer imple-This article presents in substance the author’s Governing Board Keynote

. This paper commences by outlining notions of creativity before examining the role of emergence in creative design. Various process models of emergence are presented; these are based on notions of additive and substitutive variables resulting in additive and substitutive schemas. Frameworks for both representation and process for a computational model of creative design are presented. The representational framework is based on design prototypes whilst the process framework is based on an evolutionary model. The computational model brings both representation and process together. 1. Creativity in Design In order to develop and describe any model of creativity in design we need to have an acceptable conception of design. Design, in one sense, can be conceived of as a purposeful, constrained, decision making, exploration and learning activity. Decision making implies a set of variables, the values of which have to be decided. Search is the common process used in decision making. Explor...

This paper draws a distinction between search and exploration in design. Search is a process for locating values of variables in a defined state space whilst exploration is a process for producing state spaces. The paper proceeds to elaborate two exploration processes applicable in computer-aided design: emergence and evolutionary combination. 1. Introduction

This paper presents a new feature extraction algorithm called Power-Normalized Cepstral Coefficients (PNCC) that is based on auditory processing. Major new features of PNCC processing include the use of a power-law nonlinearity that replaces the traditional log nonlinearity used for MFCC coefficients, and a novel algorithm that suppresses background excitation by estimating SNR based on the ratio of the arithmetic to geometric mean power, and subtracts the inferred background power. Experimental results demonstrate that the PNCC processing provides substantial improvements in recognition accuracy compared to MFCC and PLP processing for various types of additive noise. The computational cost of PNCC is only slightly greater than that of conventional MFCC processing. Index Terms: Robust speech recognition, physiological modeling, rate-level curve, power function, ratio of arithmetic mean to geometric mean, power distribution normalization 1.

A memory-based scaling model—ANCHOR—is proposed and tested. The perceived magnitude of the target stimulus is compared with a set of anchors in memory. Anchor selection is probabilistic and sensitive to similarity, base-level strength, and recency. The winning anchor provides a reference point near the target and thereby converts the global scaling problem into a local comparison. An explicit correction strategy determines the final response. Two incremental learning mechanisms update the locations and base-level activations of the anchors. This gives rise to sequential, context, transfer, practice, and other dynamic effects. The scale unfolds as an adaptive map. A hierarchy of models is tested on a battery of quantitative measures from 2 experiments in absolute identification and category rating. Category rating is a widely used method of data collection in experimental psychology. Ratings come in a wide variety of guises: psychophysical scales, similarity judgments, typicality judgments, confidence ratings, attitude questionnaires, health selfreports, and many others. The participants in all these tasks are asked to rate things using an ordered set of categories such as 1,..., 7 or strongly agree,..., strongly disagree. Most people

Ss lifted pairs of weights simultaneously, one in each hand, and judged either the difference, ratio, or average heaviness of the t\vo weights. Data for the difference and ratio tasks were in general agreement with subtractive and ratio models, but the averaging data showed discrepancies from the constant-weight averaging model similar to those reported in previous psychophysical research. Rescaling was ruled out for the averaging data, because responses to pairs of equal weight were a linear function of subtractive model scale values derived from the difference task data. Scale values for the ratio and difference task data were related exponentially, as were the responses to the pairs, consistent with Torgerson’s conjecture that Ss do not distinguish "differences " from "ratios. " They appear to use the same composition rule but different output functions, depending on the procedures for responding. The scale convergence criterion can thus prevent inappropriate rescaling when a model fails and can dictate rescaling even when a model fits. Traditionally, psychophysics was defined as the study of the relationships between physical stimuli and subjective impressions. A popular, contemporary type of psychophysical scaling, such as that advocated by Stevens (1957, 1971), can be represented as in Fig. 1A. In this schema, H represents the psychophysical function

Speakers may use pitch accents as pointers to new information, or as signals of a contrast relation between the accented item and a limited set of alternatives. There is no consensus in the literature whether a separately identifiable contrastive accent exists. Some studies report that contrastive accents are more emphatic than newness accents and have a different melodic shape. In other studies, however, it is maintained that contrastiveness can only be determined by looking at how accents are distributed in an utterance. It is argued that these two contrasting views on contrastiveness can be reconciled by showing that they apply on different levels. To this end, accent patterns were obtained in a (semi-)spontaneous way via a dialogue game (Dutch) in which two participants had to describe coloured figures in consecutive turns. By varying the sequential order, target descriptions ("blue square") were collected in four contexts: no contrast (all new), contrast in the adje...

ABSTRACT: Cognitive map-design research has the goal of understanding human cognition in order to improve the design and use of maps. As a systematic sub-discipline of cartography, cognitive mapdesign research is a phenomenon of the twentieth century, specifically the latter half. Robinson’s The Look of Maps, published in 1952, played a seminal role in the genesis of cognitive map-design research in several countries, but it had interesting precursors. Empirical work that followed from The Look of Maps included psychophysical studies of graduated circles and studies of eye movements during map reading. Theoretical work that followed included a variety of cognitive theories but especially the development of the communication model as a comprehensive framework for scientific cartography. I chart the changing fortunes of cognitive map-design research after The Look of Maps and offer explanations for these changes. I also consider the legacy of cognitive map-design research—ways in which it has or has not mattered. I conclude with a list of questions suggested, but not decisively answered, by this exploratory essay.

SYNOPSIS. Frequently, animals must choose between more immediate, smaller rewards and more delayed, but larger rewards. For example, they often must decide between accepting a smaller prey item versus continuing to search for a larger one, or between entering a leaner patch versus travelling to a richer patch that is further away. In both situations, choice of the more immediate, but smaller reward may be interpreted as implying that the value of the later reward is discounted; that is, the value of the later reward decreases as the delay to its receipt increases. This decrease in value may occur because of the increased risk involved in waiting for rewards, or because of the decreased rate of reward associated with increased waiting time. The present research attempts to determine the form of the relation between value and delay, and examines implications of this relation for mechanisms underlying risk-sensitive foraging. Two accounts of the relation between value and delay have been proposed to describe the decrease in value resulting from increases in delay: