Swarm intelligence in the problems of detecting anomalies and states of natural-technical systems and objects

An approach to solving the problem of detecting and classifying anomalies and states of natural-technical systems and objects using swarm intelligence methods is considered. The main directions of development of the proposed approach include ant algorithms, bee swarm algorithms, and the particle swarm method. The structure of the swarm intelligence system of decision support based on collective preference rules is proposed. The application of the proposed approach makes it possible to optimize the processes of processing, analysis, integration of heterogeneous data, to increase the sensitivity, reliability and efficiency of decisions made.

Child-Like Adults: Dual-Task Effects on Collective vs. Distributive Sentence Interpretations

In this work, we consider a recent proposal that claims that the preferred interpretation of sentences containing definite plural expressions, such as “The boys are building a snowman,” is not determined by semantic composition but is pragmatically derived via an implicature. Plural expressions can express that each member of a group acts individually (distributive interpretation) or that the group acts together (collective interpretation). While adults prefer collective interpretations for sentences that are not explicitly marked for distributivity by the distributive marker each, children do not show this preference. One explanation is that the adult collective preference for definite plurals arises due to a conversational implicature. If implicature calculation requires memory resources, children may fail to calculate the implicature due to memory limitations. This study investigated whether loading Dutch-speaking adults' working memory, using a dual task, would elicit more child-like distributive interpretations, as would be predicted by the implicature account. We found that loading WM in adults did lead to response patterns more similar to children. We discuss whether our results offer a plausible explanation for children's development of an understanding of distributivity and how our results relate to recent debates on the role of cognitive resources in implicature calculation.

Collective preference learning in the best-of-n problem

Decentralised autonomous systems rely on distributed learning to make decisions and to collaborate in pursuit of a shared objective. For example, in swarm robotics the best-of-n problem is a well-known collective decision-making problem in which agents attempt to learn the best option out of n possible alternatives based on local feedback from the environment. This typically involves gathering information about all n alternatives while then systematically discarding information about all but the best option. However, for applications such as search and rescue in which learning the ranking of options is useful or crucial, best-of-n decision-making can be wasteful and costly. Instead, we investigate a more general distributed learning process in which agents learn a preference ordering over all of the n options. More specifically, we introduce a distributed rank learning algorithm based on three-valued logic. We then use agent-based simulation experiments to demonstrate the effectiveness of this model. In this context, we show that a population of agents are able to learn a total ordering over the n options and furthermore the learning process is robust to evidential noise. To demonstrate the practicality of our model, we restrict the communication bandwidth between the agents and show that this model is also robust to limited communications whilst outperforming a comparable probabilistic model under the same communication conditions.

Groovin’ to the Cultural Beat: Preferences for Danceable Music Represent Cultural Affordances for Anger Experiences and Expressions

Music is frequently used to regulate one’s affect. Yet, societal affordances for emotions vary across cultures, meaning that music preferences should reflect these differences in emotional affordances as representations of culture (cultural products). By quantifying music through musical features, we can examine the cultural psychological processes involved in music preferences. The exploratory section (Studies 1 and 2) identified differences in music preferences for East-Asian and Western popular music on Spotify (combined N = 1006644). In interpreting these results, we developed a theory on danceability as a music feature, that represents cultural affordances for high arousal emotions. Subsequent confirmatory studies (Studies 3-6) tested this theory by examining danceability and the role of emotion in music preferences through: participant self-reported preferences for music arousal and music function (Study 3: N = 268 participants from Singapore and the US), arousal and cultural orientation in lyrics (Study 4: N = 343 songs from Singapore, Hong Kong, US and Canada), emotion prevalence and popular music preference in 60 countries (Study 5, N = 3000 songs), and self-reported music preference and danceability in 13 countries (Study 6, N = 1331 participants). Across these studies, danceability was robustly associated with anger, and this relationship suggests danceability feature preferences may be representative of cultural affordances for anger experiences and expressions. We argue that this collective preference is due to high danceability music having a cathartic effect on the downregulation of everyday high-arousal negative emotions, which differs across cultures.

Collective preferences in Dutch revealed by a covered-box experiment

Sentences with plural expressions are compatible with distributive and collective interpretations. Adults generally prefer collective interpretations, whereas children do not. Dotlačil (2010) argues that the adult collective preference arises via an implicature. Adults can reason about alternative utterances with the distributive marker each, thereby ruling out distributive interpretations in favor of collective interpretations. Experiment 1 used the covered-box paradigm to investigate whether adults and children make the comparisons predicted by Dotlačil’s implicature account. Adults’ responses suggest that they made comparisons with internally generated alternatives, supporting the implicature account. Moreover, children seem to do so from around 11 years old onwards, after they have learned the distributive character of each. Experiment 2 excluded the possibility that our results in Experiment 1 were influenced by participants’ exposure to both collective and distributive pictures, making the collective interpretation more salient. Both experiments thus point towards an implicature underlying the adult collective preference.

TWO-STAGE PRIORITIZATION PROCEDURE FOR MULTIPLICATIVE AHP-GROUP DECISION MAKING

In this paper, we propose two-stage prioritization procedure (TSPP) for multiplicative Analytic Hierarchy Process-group decision making (AHP-GDM), which involves determining the group priority vector based on the individual pair-wise comparison matrices (PCMs), simultaneously considering the consensus and consistency of the individual PCMs. The first stage of the TSPP involves checking and revising the individual PCMs for reaching the acceptable consensus and consistency. The second stage of the TSPP involves estimating the group priority vector using Bayesian approach. The main characteristics of the proposed TSPP are as follows: 1) It makes full use of the prior information as well as the sample information during the Bayesian revision of the individual PCMs and the Bayesian estimation of the group priority vector; 2) It ensures that the revised individual PCMs reach the acceptable consensus and consistency; 3) It enriches the aggregation methods for the collective preference in multiplicative AHP-GDM. Finally, two numerical examples are used to evaluate the applicability and effectiveness of the proposed TSPP by the comparisons with several other methods.

Voting Method Based on an Average Gap Assessment

The theory of social choice is the study of voting methods. In the literature manystudies have been conducted for the development of a fair voting system, that is to say a voting method that allows to aggregate the individual preferences in a collective preference representing in the most possible faithfull way individual preferences. Yet some voting methods do not allow to obtain a consensus. So there are a lot of paradoxes in electoral systems and related results in the theory of social choice are also paradoxical. This is the case, for example, with Arrow’s theorem showing that no voting method can simultaneously verify a restricted list of roperties that are desirable in a democratic political system. That is to mean that the search for a system that makes it possible to reach a consensus remains a concern in the theory of social choice. In this article we have combined various voting methods based on grading, scoring or approving to contribute to literature with a new voting system filling fair properties.

Supplier Selection by Extended TOPSIS to Obtain the Ideal Compromise Solution in Group Decision Making

In the current literature, there are several studies, which the supplier selection is typically a Multi Criteria Group Decision Making problem. Several solutions for the above problem are proposed (from simple approaches; like, Borda, Condorcet, etc., to complex ones; like, Multiple Criteria Decision Making model combined with intuitionistic fuzzy set, etc.). To solve this problem, different method (particularly, extended TOPSIS method) are proposed in this paper. Firstly, we have used TOPSIS to find the individual preference ordering, then, we have used the extended version of this method to find the collective preference orderings. In addition, this model is capable of considering the expert weights. Finally, the proposed approach is compared with an existed approach (i.e., TOPSIS and Borda's function). Compared results show the advantage of our extended model over previous one.