The purpose of urban planning gaming is to make experiments in decision-making for urban plans. In order to produce satisfactory results of training in gamings, it is necessary to develop computer assisted gaming support systems. In this paper, firstly, we propose a project planning system as one of gaming support systems which interactively assists players to make their action programs by coordinating them in project programs which compose an urban plan. Secondly, we present the logical foundation on design of project planning systems, which is an assumption-based temporal reasoning method named ASTRON. We describe the knowledge representation, the reasoning procedure of ASTRON and its application to project planning. Lastly we describe a trial implementation of project planning system named PASTERE which is built on the knowledge system building tool WORLDS.
A least squares procedure called GIPSCAL (a Generalized Inner Product multidimensional SCALing) is proposed which extends Chino's ASYMSCAL into higher dimensions than three. GIPSCAL fits the inner product of two vectors and the area of the parallelogram spanned by these vectors, respectively, for the symmetric and skew-symmetric parts of observed similarity judgements. It is shown that GIPSCAL has a very desirable property that the geometrical interpretation of asymmetric parts in similarity judgements is reducible to that of the area of the parallelogram spanned by vectors in two dimensions. It is also shown that GIPSCAL permits a social psychological justification for the cause of asymmetry. Relation to distance model is discussed. Examples of application are given to demonstrate the feasibility of the model.
A generalized version of Takane and Carroll's (1981) (Psychometrika, 46, 389-405) scaling model is developed to analyze rank order data. This model assigns to each stimulus n (the number of stimuli) different scale values each of which is to be utilized at its respective occasion of successive first choice in the ranking task. The n scale values assigned to a stimulus is predicted by using the cumulative binominal distribution function for an assumed set of n-1 Bernoulli trials of a simple judgment about the same attribute of that stimulus as is to be scaled from the ranking data. Examples of the application of the model are reported. They have demonstrated that the generalized model can account for all the data sets examined better than the original one.
The characteristics of human intuitive reasoning in estimating posterior probability can often be clarified through counterintuitive problems. A modified version of the “problem of three prisoners” (Shimojo & Ichikawa, 1989) is a very difficult Bayesian problem. Most subjects cannot yield the normative answer, and they do not intuitively accept it even after they understand the solution based on Bayes' theorem. However, it has been pointed out that this problem has some ambiguity on a conditional probability, which is critical to solve it. In the present study, the subjects were first required to determine a value of the ambiguous parameter freely and then solve the problem. This pre-manipulation did not improve their performance: Most of them could not give the answer in accordance with the parameter they set for themselves. Moreover, an additional questionnaire revealed that many subjects had a crucial fallacy on the relation between prior and posterior probabilities. It is argued that the difficulty of the problem lies not in setting a value of the parameter but in the subjects' erroneous beliefs about the nature of probability.
A method for estimating the total quantity of goods distributed in a market is presented by the use of a polynomial regression curve on the plane where the y-coordinate consists of the rates of goods for their product numbers. Two kinds of estimators for the above-mentioned total quantity are proposed with investigating their asymptotic properties. As a practical example, estimating the total quantity of beer cases in a market is considered.
As a continuation of Tanaka and Odaka (1989a), which proposed a procedure for sensitivity analysis in the iterative principal factor analysis (PFA), influence functions are derived for sensitivity analysis in two procedures of noniterative PFA. A numerical investigation is carried out to study the validity and usefulness of the proposed procedures and a comparison is made among various procedures of PFA from the viewpoint of sensitivity.
Central vision and peripheral vision are two of main components of visual perception. The functional differences between the two visions are considered with two points of view: the physiological receptive field and the psychological perceptive field. The authors propose a retinal model of lateral inhibition. The output is discrete summation of ganglion cell responses through the Difference of Gaussian (DOG) function of the coupling width. The coupling width is given by the size of receptive field, according to Fisher's findings that the distribution of the ganglion cell density decreases from the fovea to the peripheral area. Sampling points of the summation correspond to the positions of the ganglion cells, so that a number of points in all the same in each receptive field. The coupling width was determined by the data of Jung and Spillmann's (1970) psychological experiment. As an application of this model, the Hermann grid illusion is quantitatively explained.
For the well-known British occupational mobility data describing the cross-classification of father's and son's occupational status categories, the quasi-uniform association (QU) model considered by Goodman (1979a, 1981b) fits well. This paper gives decompositions for the QU model and also shows that for the British data one of the decomposed models is preferable to the QU model though the QU model has a good fit.