Cognitive Systems Research最新文献_第6页

On the logic of agent’s emotions 论代理人的情感逻辑

IF 2.1 3区心理学

Cognitive Systems Research Pub Date : 2024-09-06 DOI: 10.1016/j.cogsys.2024.101281

Yuanyi Wang , Zhen Liu , Tingting Liu , Alexei V. Samsonovich , Valentin V. Klimov

引用次数: 0

Adaptive network modeling for joint action and memory recall for elderly by detecting interpersonal synchrony 通过检测人际同步，为老年人的联合行动和记忆回忆建立自适应网络模型

IF 2.1 3区心理学

Cognitive Systems Research Pub Date : 2024-08-30 DOI: 10.1016/j.cogsys.2024.101280

Yijie Xu , Sophie C.F. Hendrikse , Jan Treur , Peter H.M.P. Roelofsma

{"title":"Adaptive network modeling for joint action and memory recall for elderly by detecting interpersonal synchrony","authors":"Yijie Xu , Sophie C.F. Hendrikse , Jan Treur , Peter H.M.P. Roelofsma","doi":"10.1016/j.cogsys.2024.101280","DOIUrl":"10.1016/j.cogsys.2024.101280","url":null,"abstract":"<div><p>This paper explores the potential of adaptive network modeling for joint action and memory recall among elderly through detecting interpersonal synchrony. With the aging population increasing, there is a crucial need to focus on the health and social interaction of older adults. Based on research of the significance of social interaction and memory use for the elderly, as well as the role of interpersonal synchrony in joint action, this paper aims to analyse computationally how to enhance positive effects of social interactions among older individuals by applying an adaptive network model. The research examines the concept of interpersonal synchrony and its impact on joint action, memory, and emotional well-being in elderly populations. Through simulation experiments and analysis, the study demonstrates the potential benefits for music in memory recall for older adults with cognitive decline, highlighting the importance of social interaction and emotional resonance. This study offers a valuable contribution to understanding and improving social interactions and memory recall among the elderly.</p></div>","PeriodicalId":55242,"journal":{"name":"Cognitive Systems Research","volume":"88 ","pages":"Article 101280"},"PeriodicalIF":2.1,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1389041724000743/pdfft?md5=cf7f62f35c4e17b003e1165735b663ab&pid=1-s2.0-S1389041724000743-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142117425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A motivational-based learning model for mobile robots 基于动机的移动机器人学习模型

IF 2.1 3区心理学

Cognitive Systems Research Pub Date : 2024-08-28 DOI: 10.1016/j.cogsys.2024.101278

Letícia Berto , Paula Costa , Alexandre Simões , Ricardo Gudwin , Esther Colombini

{"title":"A motivational-based learning model for mobile robots","authors":"Letícia Berto , Paula Costa , Alexandre Simões , Ricardo Gudwin , Esther Colombini","doi":"10.1016/j.cogsys.2024.101278","DOIUrl":"10.1016/j.cogsys.2024.101278","url":null,"abstract":"<div><p>Humans have needs motivating their behavior according to intensity and context. However, we also create preferences associated with each action’s perceived pleasure, which is susceptible to changes over time. This makes decision-making more complex, requiring learning to balance <em>needs</em> and preferences according to the context. To understand how this process works and enable the development of robots with a motivational-based learning model, we computationally model a motivation theory proposed by Hull. In this model, the agent (an abstraction of a mobile robot) is motivated to keep itself in a state of homeostasis. We introduced hedonic dimensions to explore the impact of preferences on decision-making and employed reinforcement learning to train our motivated-based agents. In our experiments, we deploy three agents with distinct energy decay rates, simulating different metabolic rates, within two diverse environments. We investigate the influence of these conditions on their strategies, movement patterns, and overall behavior. The findings reveal that agents excel at learning more effective strategies when the environment allows for choices that align with their metabolic requirements. Furthermore, we observe that incorporating pleasure as a component of the motivational mechanism affects behavior learning, particularly for agents with regular metabolisms depending on the environment. Our study also unveils that, when confronted with survival challenges, agents prioritize immediate <em>needs</em> over pleasure and equilibrium. These insights shed light on how robotic agents can adapt and make informed decisions in demanding scenarios, demonstrating the intricate interplay between motivation, pleasure, and environmental context in autonomous systems.</p></div>","PeriodicalId":55242,"journal":{"name":"Cognitive Systems Research","volume":"88 ","pages":"Article 101278"},"PeriodicalIF":2.1,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142128212","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A universal knowledge model and cognitive architectures for prototyping AGI 用于 AGI 原型开发的通用知识模型和认知架构

IF 2.1 3区心理学

Cognitive Systems Research Pub Date : 2024-08-28 DOI: 10.1016/j.cogsys.2024.101279

Artem Sukhobokov , Evgeny Belousov , Danila Gromozdov , Anna Zenger , Ilya Popov

{"title":"A universal knowledge model and cognitive architectures for prototyping AGI","authors":"Artem Sukhobokov , Evgeny Belousov , Danila Gromozdov , Anna Zenger , Ilya Popov","doi":"10.1016/j.cogsys.2024.101279","DOIUrl":"10.1016/j.cogsys.2024.101279","url":null,"abstract":"<div><p>The article identified 56 cognitive architectures for creating general artificial intelligence (AGI) and proposed a set of interrelated functional blocks that an agent approaching AGI in its capabilities should possess. Since the required set of blocks is not found in any of the existing architectures, the article proposes a reference cognitive architecture for intelligent systems approaching AGI in their capabilities. As one of the key solutions within the framework of the architecture, a universal method of knowledge representation is proposed, which allows combining various non-formalized, partially and fully formalized methods of knowledge representation in a single knowledge base, such as texts in natural languages, images, audio and video recordings, graphs, algorithms, databases, neural networks, knowledge graphs, ontologies, frames, essence-property-relation models, production systems, predicate calculus models, conceptual models, and others. To combine and structure various fragments of knowledge, archigraph model are used, constructed as a development of annotated metagraphs. As other components, the reference cognitive architecture being developed includes following modules: machine consciousness, machine subconsciousness, interaction with the external environment, a goal management, an emotional control, social interaction, reflection, ethics, worldview, learning, monitoring, statement problems, solving problems, self-organization and meta learning. Based on the composition of the proposed reference architecture modules, existing cognitive architectures containing the following modules were analyzed: machine consciousness, machine subconsciousness, reflection, worldview.</p></div>","PeriodicalId":55242,"journal":{"name":"Cognitive Systems Research","volume":"88 ","pages":"Article 101279"},"PeriodicalIF":2.1,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142150798","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Hebbian spatial encoder with adaptive sparse connectivity 具有自适应稀疏连接性的海比空间编码器

IF 2.1 3区心理学

Cognitive Systems Research Pub Date : 2024-08-22 DOI: 10.1016/j.cogsys.2024.101277

Petr Kuderov , Evgenii Dzhivelikian , Aleksandr I. Panov

{"title":"Hebbian spatial encoder with adaptive sparse connectivity","authors":"Petr Kuderov , Evgenii Dzhivelikian , Aleksandr I. Panov","doi":"10.1016/j.cogsys.2024.101277","DOIUrl":"10.1016/j.cogsys.2024.101277","url":null,"abstract":"<div><p>Biologically plausible neural networks have demonstrated efficiency in learning and recognizing patterns in data. This paper proposes a general online unsupervised algorithm for spatial data encoding using fast Hebbian learning. Inspired by the Hierarchical Temporal Memory (HTM) framework, we introduce the <em>SpatialEncoder</em> algorithm, which learns the spatial specialization of neurons’ receptive fields through Hebbian plasticity and k-WTA (<em>k</em> winners take all) inhibition. A key component of our model is a two-part synaptogenesis algorithm that enables the network to maintain a sparse connection matrix while adapting to non-stationary input data distributions. In the MNIST digit classification task, our model outperforms the HTM SpatialPooler in terms of classification accuracy and encoding stability. Compared to another baseline, a two-layer artificial neural network (ANN), our model achieves competitive classification accuracy with fewer iterations required for convergence. The proposed model offers a promising direction for future research on sparse neural networks with adaptive neural connectivity.</p></div>","PeriodicalId":55242,"journal":{"name":"Cognitive Systems Research","volume":"88 ","pages":"Article 101277"},"PeriodicalIF":2.1,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142083559","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Modeling quick autonomous response for virtual characters in safety education games 为安全教育游戏中的虚拟角色建立快速自主响应模型

IF 2.1 3区心理学

Cognitive Systems Research Pub Date : 2024-08-15 DOI: 10.1016/j.cogsys.2024.101276

Tingting Liu , Zhen Liu , Yuanyi Wang , Yanjie Chai

{"title":"Modeling quick autonomous response for virtual characters in safety education games","authors":"Tingting Liu , Zhen Liu , Yuanyi Wang , Yanjie Chai","doi":"10.1016/j.cogsys.2024.101276","DOIUrl":"10.1016/j.cogsys.2024.101276","url":null,"abstract":"<div><p>Serious games have a wide range of applications. Modeling virtual character behaviors and emotions is a challenging task in developing serious games. To generate real-time responses, behavioral and emotional models must be simple and effective. Existing studies have paid little attention to the semantic understanding of virtual characters to external stimuli and have not effectively linked perceived semantics and motivation. This paper proposes a cognitive structure for the virtual character. The structure contains multiple modules: perception, personality, motivation, behavior, and emotion. Based on psychological theory, a semantic table that connects external stimuli, motivations, behaviors, and emotions is designed for each virtual character. Perceptivity is introduced to measure the degree of perception. According to Maslow’s motivation theory, a quantitative description of motivation is given and a discriminating method is proposed to generate behaviors and emotions. A prototype of a serious game is developed to verify the validity of the proposed method. The experimental results show that the proposed method can simulate the behavior and emotion of virtual characters in real time and will enhance the immersion of serious games.</p></div>","PeriodicalId":55242,"journal":{"name":"Cognitive Systems Research","volume":"88 ","pages":"Article 101276"},"PeriodicalIF":2.1,"publicationDate":"2024-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142270576","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A multi-agent motion simulation method for emergency scenario deduction 用于应急场景推演的多代理运动模拟方法

IF 2.1 3区心理学

Cognitive Systems Research Pub Date : 2024-08-14 DOI: 10.1016/j.cogsys.2024.101275

Jiale Wang , Zhen Liu , Tingting Liu , Yuanyi Wang

{"title":"A multi-agent motion simulation method for emergency scenario deduction","authors":"Jiale Wang , Zhen Liu , Tingting Liu , Yuanyi Wang","doi":"10.1016/j.cogsys.2024.101275","DOIUrl":"10.1016/j.cogsys.2024.101275","url":null,"abstract":"<div><p>Simulating crowd motion in emergency scenarios remains a challenge in computer graphics due to crowd heterogeneity and environmental complexity. However, existing crowd simulation methods homogenize the agent model and simplify target selection and motion navigation of emergency crowds. To address these problems, we propose a multi-agent motion simulation method for emergency scenario deduction. First, we propose a multi-agent model to simulate crowd heterogeneity. This model includes a personality-based heterogeneous agent model and an agent perception model that considers vision, hearing, and familiarity with the environment. Second, we propose a target selection strategy based on the motion patterns of actual pedestrians. This strategy employs mathematical models and our agent perception model to guide agents in selecting appropriate targets. Finally, we propose a global navigation algorithm that combines random sampling with heuristic search methods. Concurrently, we use our multi-agent model to adjust the agent’s local motion planning to deduce the motion states of emergency crowds naturally. Experimental results validate that our method can realistically and reasonably simulate crowd motion in emergency scenarios.</p></div>","PeriodicalId":55242,"journal":{"name":"Cognitive Systems Research","volume":"88 ","pages":"Article 101275"},"PeriodicalIF":2.1,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142164456","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Crowdsourced geolocation: Detailed exploration of mathematical and computational modeling approaches 众包地理定位：数学和计算建模方法的详细探索

IF 2.1 3区心理学

Cognitive Systems Research Pub Date : 2024-07-31 DOI: 10.1016/j.cogsys.2024.101266

Rocco Ballester , Yanis Labeyrie , Mehmet Oguz Mulayim , Jose Luis Fernandez-Marquez , Jesus Cerquides

{"title":"Crowdsourced geolocation: Detailed exploration of mathematical and computational modeling approaches","authors":"Rocco Ballester , Yanis Labeyrie , Mehmet Oguz Mulayim , Jose Luis Fernandez-Marquez , Jesus Cerquides","doi":"10.1016/j.cogsys.2024.101266","DOIUrl":"10.1016/j.cogsys.2024.101266","url":null,"abstract":"<div><p>In emergency situations, social media platforms produce a vast amount of real-time data that holds immense value, particularly in the first 72 h following a disaster event. Despite previous efforts, efficiently determining the geographical location of images related to a new disaster remains an unresolved operational challenge. Currently, the state-of-the-art approach for dealing with these first response mapping is first filtering and then submitting the images to be geolocated to a volunteer crowd, assigning the images randomly to the volunteers. In this work, we extend our previous paper (Ballester et al., 2023) to explore the potential of artificial intelligence (AI) in aiding emergency responders and disaster relief organizations in geolocating social media images from a zone recently hit by a disaster. Our contributions include building two different models in which we try to (i) be able to learn volunteers’ error profiles and (ii) intelligently assign tasks to those volunteers who exhibit higher proficiency. Moreover, we present methods that outperform random allocation of tasks, analyze the effect on the models’ performance when varying numerous parameters, and show that for a given set of tasks and volunteers, we are able to process them with a significantly lower annotation budget, that is, we are able to make fewer volunteer solicitations without losing any quality on the final consensus.</p></div>","PeriodicalId":55242,"journal":{"name":"Cognitive Systems Research","volume":"88 ","pages":"Article 101266"},"PeriodicalIF":2.1,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141931768","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

EmpCI: Empathetic response generation with common sense and empathetic intent EmpCI：用常识和意图生成富有同情心的反应

IF 2.1 3区心理学

Cognitive Systems Research Pub Date : 2024-07-25 DOI: 10.1016/j.cogsys.2024.101267

Xun Wang , Tingting Liu , Zhen Liu , Zheng Fang

{"title":"EmpCI: Empathetic response generation with common sense and empathetic intent","authors":"Xun Wang , Tingting Liu , Zhen Liu , Zheng Fang","doi":"10.1016/j.cogsys.2024.101267","DOIUrl":"10.1016/j.cogsys.2024.101267","url":null,"abstract":"<div><p>Empathy plays an important role in human conversations as an ability that enables individuals to understand the emotions and situations of others. Integrating empathy into dialogue systems is a crucial step in making them humanized. Relevant psychological studies have shown that a complete, high-quality empathetic dialogue should consist of the following two stages: (1) Empathetic Perception: the listener needs to perceive the emotional state of the speaker from both cognitive and affective aspects; (2) Empathetic Expression: the appropriate expression is chosen to respond to the perceived information. However, many existing studies on empathetic response generation only focus on one of these stages, resulting in incomplete and insufficiently empathetic responses. To this end, we propose the EmpCI, a two-stage empathetic response generation model that utilizes commonsense knowledge and mixed empathetic intent, respectively. Specifically, we use commonsense knowledge in the first stage to enhance the model’s perception of the user’s emotion and introduce mixed empathetic intent in the second stage to generate responses with appropriate expressions for the perceived information. Finally, we evaluated the EmpCI on the EmpatheticDialogues dataset, and extensive experiment results show that the proposed model outperforms the baselines in both perceiving users’ emotions and generating empathetic responses.</p></div>","PeriodicalId":55242,"journal":{"name":"Cognitive Systems Research","volume":"88 ","pages":"Article 101267"},"PeriodicalIF":2.1,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141848637","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Typeface recognition and legibility metrics 字体识别和可读性指标

IF 2.1 3区心理学

Cognitive Systems Research Pub Date : 2024-07-24 DOI: 10.1016/j.cogsys.2024.101263

Xavier Molinero , Montserrat Tàpias , Andreu Balius , Francesc Salvadó

{"title":"Typeface recognition and legibility metrics","authors":"Xavier Molinero , Montserrat Tàpias , Andreu Balius , Francesc Salvadó","doi":"10.1016/j.cogsys.2024.101263","DOIUrl":"10.1016/j.cogsys.2024.101263","url":null,"abstract":"<div><p>In the digital age, people prefer digital content, but screen-related health concerns like eye strain and blue light emerge. Legibility gains importance in digital text, especially in fields like optometry and for those with low vision. Therefore, having good letter recognition ensures better readability of words and written language in general. This work focuses on defining three typeface legibility indices from the judgements of a group of 31 observers. Those indices are based on statistics, confusion matrices, and power indices from game theory. As far as we know, this is the first time that typeface legibility indices have been defined using game theory. These indices help us to globally assess how legible is a typeface. We apply them to three commonly used typefaces (Roboto, Helvetica and Georgia), and to a new one developed for the authors (Optotipica 5 v2022). This comparison helps us understand which typefaces are more legible according to the defined indices on digital screens. The major conclusions are: (1) The three indices are highly consistent pairwise; (2) Helvetica is the most legible typeface for uppercase letters, whilst Optotipica is the most legible for lowercase; (3) the two cases of Helvetica exhibit uniform high legibility metrics, ensuring optimal recognition regardless of letter case.</p></div>","PeriodicalId":55242,"journal":{"name":"Cognitive Systems Research","volume":"88 ","pages":"Article 101263"},"PeriodicalIF":2.1,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141779529","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0