A Model for an Affective Non-Expensive Utility-Based Decision Agent

Esteban, Pablo Gómez; Insua, David Rı́os

doi:10.1109/taffc.2017.2737979

Cited by 15 publications

(9 citation statements)

References 30 publications

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“…We manage to overcome these difficulties, simplify and model this problem into a standard operation algorithm. The practical application of the method is that readers can quickly find the positive and negative nodes in the literary work to understand the characters and plots with a small amount of manual assistance and assist decision making for writing and publishing [43]. It is a bold experiment and novel attempt for computers to understand natural language literary works.…”

Section: Discussionmentioning

confidence: 99%

Building Character Graphs and Dividing Communities in Chinese Novels Based on Graph Data Extraction: Community Division for Character Emotional Polarity Networks

et al. 2020

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Chinese authors indirectly portray real social relationships in society by incorporating their own experiences and feelings about politics, economic life, and cultural habits. Social and natural knowledge are mixed and hidden in natural literary language. Therefore, by well defining the type of original text, the pipeline for processing the text and the rules to build the graph, we can extract enough valid and useful information. Based on higher-level information, we can build a literary character graph to promote computers' comprehension of literature. The identification of opposite characters is a challenging topic because the character relationships are intricate and complex. The cryptic expression in literary works can enhance the readability of the plot, but it is obvious that it increases the cost of understanding. Even for human readers different types of characters are difficult to classify and identify, and it usually needs careful reading for several times to get the subtle differences among the characters. Though extracting knowledge from Chinese literature is a complicated and difficult topic, this paper models the graph of polar literary characters and divides polar communities by extracting polar vertices and polar edges based on the concept of literary sentiment polarity. The results show that using a long-sentence window is a good trade-off. The experiments of modern Chinese polar literature show that the accuracy of the community division method for the integrated graph polarity is obviously better than the method based on the co-occurrence network, and it can automatically match the positive and negative communities as well as build the complete graph structure. It clearly reflects the meaning of literary works from the perspective of polarity. This systematic model describes general standard operation steps for the machine to understand complex Chinese literature. The experiments conducted on seven benchmark Chinese novel datasets demonstrate that the method based on emotional polarity shows a significant improvement compared to baseline performance. Though we use Chinese datasets in this paper, the model and methods are important references for literature analysis and graph extraction in other languages. INDEX TERMS Community division, character graphs, emotional polarity, natural language processing, social network analysis.

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Section: Discussionmentioning

confidence: 99%

Building Character Graphs and Dividing Communities in Chinese Novels Based on Graph Data Extraction: Community Division for Character Emotional Polarity Networks

et al. 2020

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“…It can be argued that the trends of the overall system in the simulation process of the model evolve spontaneously from a certain point of view, and therefore researchers find some patterns in the existence of real-life consumer behavior when observing the simulation process of the agent model (Moerland et al [17]). In addition, from a technical point of view, the agent model is easier to maintain and refine, with an unlimited number of system runs and the ability to add different types of individuals or different attributes of individuals at will during the run without damaging the starting state of the system, which is in line with changes in the real consumer market (Esteban et al [18]).…”

Section: Model Construction 21 Features Of Agent-based Model Simulationmentioning

confidence: 99%

Modelling the Consumption Behaviour of Heterogeneous Consumers: A Duty-Free Shop Case Simulation Analysis

2022

Teh. vjesn.

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Duty-free shops, which have emerged in major airports, first-tier cities, free trade zones and other places, have become ideal places for not only facilitating people to buy goods but also promoting the development of the local economy, which makes the study of the heterogeneous consumer purchase behavior in duty-free stores of great importance and great practical significance. Based on this, the agent model is used to study the purchase behavior of heterogeneous consumers in duty-free stores, the structure of the agent model is proposed, the consumer submodel and situation submodel are designed, and a service recommendation is made. On this basis, the consumer behavior is simulated and analyzed both with and without considering situational factors. The following conclusions are drawn: (1) The display, the month, holidays, and other factors have an important impact on the heterogeneous consumers of duty-free stores and affect consumers' consumption behavior. (2) Salespeople's recommendation rules and consumers' purchase preferences affect consumers' purchase behavior, which has an important impact on the types and quantity of goods consumers buy.

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“…Additionally, to use affect within a decision-making process to improve the performance and attraction of a non-expensive robotic agent, Esteban and Insua [32] proposed an affective model for autonomous robots that calculated through mathematical models to infer user actions and environment evolution. The agent selected and expressed from four basic emotions and was triggered behaviors reacting to the expected or immediate human moods.…”

Section: Emotional Responsiveness In Embodied Agentsmentioning

confidence: 99%

“…This experiment involved the Mimicry Diana and Demo Diana with responsive affect in terms of non-standard facial expressions because it was in the context of a collaborative task. As a comparison, many embodied conversational agents were designed to express Ekman's [7] seven basic emotions, see [8,19,20,28,29,32]. However, these emotions are not all suitable to be expressed by an avatar in a collaborative environment.…”

Section: Design Of Appropriate Responsesmentioning

confidence: 99%

Building an Emotionally Responsive Avatar with Dynamic Facial Expressions in Human—Computer Interactions

Wang

Gaddy

Beveridge

et al. 2021

MTI

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The role of affect has been long studied in human–computer interactions. Unlike previous studies that focused on seven basic emotions, an avatar named Diana was introduced who expresses a higher level of emotional intelligence. To adapt to the users various affects during interaction, Diana simulates emotions with dynamic facial expressions. When two people collaborated to build blocks, their affects were recognized and labeled using the Affdex SDK and a descriptive analysis was provided. When participants turned to collaborate with Diana, their subjective responses were collected and the length of completion was recorded. Three modes of Diana were involved: a flat-faced Diana, a Diana that used mimicry facial expressions, and a Diana that used emotionally responsive facial expressions. Twenty-one responses were collected through a five-point Likert scale questionnaire and the NASA TLX. Results from questionnaires were not statistically different. However, the emotionally responsive Diana obtained more positive responses, and people spent the longest time with the mimicry Diana. In post-study comments, most participants perceived facial expressions on Diana’s face as natural, four mentioned uncomfortable feelings caused by the Uncanny Valley effect.

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A Model for an Affective Non-Expensive Utility-Based Decision Agent

Cited by 15 publications

References 30 publications

Building Character Graphs and Dividing Communities in Chinese Novels Based on Graph Data Extraction: Community Division for Character Emotional Polarity Networks

Building Character Graphs and Dividing Communities in Chinese Novels Based on Graph Data Extraction: Community Division for Character Emotional Polarity Networks

Modelling the Consumption Behaviour of Heterogeneous Consumers: A Duty-Free Shop Case Simulation Analysis

Building an Emotionally Responsive Avatar with Dynamic Facial Expressions in Human—Computer Interactions

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