A Tight Bound for Stochastic Submodular Cover

We show that the Adaptive Greedy algorithm of Golovin and Krause achieves an approximation bound of (ln(Q/η)+1) for Stochastic Submodular Cover: here Q is the “goal value” and η is the minimum gap between Q and any attainable utility value Q'<Q. Although this bound was claimed by Golovin and Krause in the original version of their paper, the proof was later shown to be incorrect by Nan & Saligrama. The subsequent corrected proof of Golovin and Krause gives a quadratic bound of (ln(Q/η)+1)2. A bound of 56(ln(Q/η)+1) is implied by work of Im et al. Other bounds for the problem depend on quantities other than Q and η. Our bound restores the original bound claimed by Golovin and Krause, generalizing the well-known (ln m+1) approximation bound on the greedy algorithm for the classical Set Cover problem, where m is the size of the ground set.

A parametric approximation algorithm for spatial group keyword queries

With the application of big data, various queries arise for information retrieval. Spatial group keyword queries aim to find a set of spatial objects that cover the query keywords and minimize a goal function such as the total distance between the objects and the query point. This problem is widely found in database applications and is known to be NP-hard. Efficient algorithms for solving this problem can only provide approximate solutions, and most of these algorithms achieve a fixed approximation ratio (the upper bound of the ratio of an approximate goal value to the optimal goal value). Thus, to obtain a self-adjusting algorithm, we propose an approximation algorithm for achieving a parametric approximation ratio. The algorithm makes a trade-off between the approximation ratio and time consumption enabling the users to assign arbitrary query accuracy. Additionally, it runs in an on-the-fly manner, making it scalable to large-scale applications. The efficiency and scalability of the algorithm were further validated using benchmark datasets.

Habitual Behavior Is Goal-Driven

We address the relation between goal-driven and habitual behaviors. Whereas in recent years the two have been juxtaposed, we suggest that habitual behavior is in fact goal-driven. To support this view, we show that habitual behavior is sensitive to changes in goal properties (reward contingencies), namely goal value and its expectancy of attainment. Whereas adjustment to these properties may be slower for habitual (or overlearned) than for nonhabitual behavior, this is likely due to the routinized (or automatic) nature of such behavior, characterized as it is by reduced attention to its consequences. Furthermore, we show that habitual behavior’s prolonged persistence despite its manifest detachment from the original goal likely stems from its attachment to a different goal. Thus, there is no need to postulate purposeless behavior. The view that habitual behavior is goal-driven offers an integrative account of a considerable body of evidence and is consistent with a functional account of psychological processes.

Pengembangan Produk Kursi Tunggu Multifungsi Dengan Menggunakan Metode Quality Function Deployment (QFD)

Waiting chairs that have attractive designs can give interest to the user. From observations and interviews with waiting chair users at Kadiri University, chairs used for seating cannot be moved according to the user's wishes. From the results of the customer statement questionnaire (Voice of Customer) obtained 7 attributes of consumer needs, namely Comfortable, There is a backrest, Metal material, according to body size, Easy to use, Multifunctional, Affordable price and 7 technical needs include waiting chair design, additional facilities , Material quality, Anthropometry, Product design, Additional functions, and Pricing. Improvement of multifunctional waiting chair products by looking at the HOQ analysis on the absolute important value of technical needs is 103.1, namely in product design and second is 92.4 in price determination. In the goal value, the average value of the attribute needs of consumers increases from old products to products that are developed. Keywords: Multifunctional Waiting Chair, Voice of Customer (VOC), House of Quality (HOQ), Quality Function Deployment (QFD)Kursi tunggu yang mempunyai desain menarik dapat memberikan minat bagi pengguna. Dari hasil observasi dan beberapa wawancara kepada pengguna kursi tunggu di Universitas Kadiri , kursi yang digunakan untuk tempat duduk tidak dapat dipindah sesuai keinginan pengguna. Dari hasil kuesioner pernyataan pelanggan(Voice Of Customer) didapatkan hasil 7 atribut kebutuhan konsumen, yaitu Nyaman, Terdapat sandaran, Material logam, Sesuai ukuran tubuh, Mudah dalam penggunaan, Multifungsi, Harga terjangkau serta 7 kebutuhan teknisnya antara lain Desain kursi tunggu, Fasilitas tambahan, Kualitas material, Anthropometri, Desain produk, Fungsi tambahan, dan Penentuan harga. Perbaikan produk kursi tunggu multifungsi dengan melihat analisis HOQ pada nilai absolute important kebutuhan teknis sebesar 103,1 yaitu pada Desain produk dan kedua sebesar 92,4 pada penentuan harga. Pada nilai goals, nilai rata-rata atribut kebutuhan konsumen meningkat dari produk lama ke produk yang dikembangkan. Kata Kunci : Kursi Tunggu Multifungsi, Voice Of Customer(VOC), House Of Quality(HOQ), Quality Function Deployment(QFD)

The Subjective Value of Cognitive Effort is Encoded by a Domain-General Valuation Network

SummaryCognitive control is necessary for goal-directed behavior, yet people treat control as costly, discounting goal value by cognitive demands in a similar manner as they would for delayed or risky outcomes. It is unclear, however, whether a putatively domain-general valuation network implicated in other cost domains also encodes the subjective value (SV) of cognitive effort. Here, we demonstrate that a valuation network, centered on the ventromedial prefrontal cortex and ventral striatum, also encodes SV during cognitive effort-based decision-making. We doubly dissociate this network from a primarily frontoparietal network recruited as a function of decision difficulty. We also find evidence that SV signals predict choice and are influenced by state and trait motivation, including sensitivity to reward and anticipated task performance. These findings unify cognitive effort with other cost domains, and inform physiological mechanisms of SV representations underlying the willingness to expend cognitive effort.

Use of analogies, metaphors, and similes by students and reviewers at an undergraduate architectural design review

This study investigates the use of similarities in the form of analogy, metaphor, and simile by students and reviewers in an undergraduate architectural design review. In contrast to studies conducted in vitro settings, this study emphasizes the importance of studying analogies, metaphors, and similes in a natural setting. All similarity relationships were coded according to their type, the level of expertise, range, frequency, goal, value judgment, and depth. The results indicate that analogies, metaphors, and similes were used spontaneously and without any difficulty by both reviewers and students. Reviewers, however, were almost twice as likely to evoke similarities. Metaphor was the most frequently used similarity relationship among the three. It was found that there was a significant relationship between the level of expertise and type of similarity, with students more likely to use analogies and less likely to use similes. It was also found that goal is the most important factor, with a significant relation to all other variables, and that embodiment is often invoked in both students’ and reviewers’ metaphors. We conclude that design education should take full advantage of students’ natural ability to benefit from similarity relationships.

Thalamocortical and corticothalamic pathways differentially contribute to goal-directed behaviors in the rat

Highly distributed neural circuits are thought to support adaptive decision-making in volatile and complex environments. Notably, the functional interactions between prefrontal and reciprocally connected thalamic nuclei areas may be important when choices are guided by current goal value or action-outcome contingency. We examined the functional involvement of selected thalamocortical and corticothalamic pathways connecting the dorsomedial prefrontal cortex (dmPFC) and the mediodorsal thalamus (MD) in the behaving rat. Using a chemogenetic approach to inhibit projection-defined dmPFC and MD neurons during an instrumental learning task, we show that thalamocortical and corticothalamic pathways differentially support goal attributes. Both pathways participate in adaptation to the current goal value, but only thalamocortical neurons are required to integrate current causal relationships. These data indicate that antiparallel flow of information within thalamocortical circuits may convey qualitatively distinct aspects of adaptive decision-making and highlight the importance of the direction of information flow within neural circuits.

A Hybrid Approach for Modular Neural Network Design Using Intercriteria Analysis and Intuitionistic Fuzzy Logic

Intercriteria analysis (ICA) is a new method, which is based on the concepts of index matrices and intuitionistic fuzzy sets, aiming at detection of possible correlations between pairs of criteria, expressed as coefficients of the positive and negative consonance between each pair of criteria. Here, the proposed method is applied to study the behavior of one type of neural networks, the modular neural networks (MNN), that combine several simple neural models for simplifying a solution to a complex problem. They are a tool that can be used for object recognition and identification. Usually the inputs of the MNN can be fed with independent data. However, there are certain limits when we may use MNN, and the number of the neurons is one of the major parameters during the implementation of the MNN. On the other hand, a high number of neurons can slow down the learning process, which is not desired. In this paper, we propose a method for removing part of the inputs and, hence, the neurons, which in addition leads to a decrease of the error between the desired goal value and the real value obtained on the output of the MNN. In the research work reported here the authors have applied the ICA method to the data from real datasets with measurements of crude oil probes, glass, and iris plant. The method can also be used to assess the independence of data with good results.