Cognitive Systems Research最新文献

{"title":"Bilateral Turing Test: Assessing machine consciousness simulations","authors":"Ge Wang,&nbsp;Xianhong Li,&nbsp;Shenghua Xie","doi":"10.1016/j.cogsys.2024.101299","DOIUrl":"10.1016/j.cogsys.2024.101299","url":null,"abstract":"<div><div>Recent advancements in Artificial Intelligence (AI) have brought discussions on machine consciousness back to the forefront. However, methodologies for assessing machine consciousness simulations remain highly constrained and lack consensus. This study introduces the Bilateral Turing Test, a thought experiment to assess machine consciousness simulations based on a functionalist perspective, focusing on external behavior and cognitive characteristics associated with consciousness. The test involves both machines and humans participating as judges in an enhanced Turing Test, and compares the external behavior of machine-simulated consciousness with the behavior of human consciousness. We derive the experimental principles via three theoretical propositions reflecting the human–machine cognitive relationship and elucidate the basic conditions and procedures of the thought experiment. A systematic measure is employed to evaluate emulation against human benchmarks, and we establish a statistical threshold for successful consciousness simulations. Our study provides a comprehensive framework for redefining machine consciousness simulations and enhancing interdisciplinary conversations across computer science, neuroscience, and philosophy. This framework also advances bottom-up approaches for assessing machine consciousness simulations and provides pivotal insights into human–machine interaction dynamics.</div></div>","PeriodicalId":55242,"journal":{"name":"Cognitive Systems Research","volume":"88 ","pages":"Article 101299"},"PeriodicalIF":2.1,"publicationDate":"2024-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142427174","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}

{"title":"An adaptive dynamical system model for development of schizophrenia: Epigenetics and false memories","authors":"Ilma Jaganjac ,&nbsp;Sophie C.F. Hendrikse ,&nbsp;Jan Treur","doi":"10.1016/j.cogsys.2024.101288","DOIUrl":"10.1016/j.cogsys.2024.101288","url":null,"abstract":"<div><div>This paper introduces a fifth-order adaptive dynamical system model represented as a self-modelling network model to understand the role of epigenetic factors in developing schizophrenia, particularly about the occurrence of false memories. Schizophrenia, affecting a significant portion of the global population, presents complex challenges due to its symptoms across cognitive, emotional, and social domains. Central to this paper is the exploration of epigenetic influences on the development of schizophrenia, with a focus on how these epigenetic factors contribute to the generation of false memories, a notable symptom of the disorder. The model assumes that early adverse experiences significantly affect hippocampal development, which is crucial for memory processes. By employing a fifth-order adaptive dynamical system model represented as a self-modelling network, this paper examines the intricate dynamics between genetic predispositions, environmental factors, and epigenetic modifications in schizophrenia. The model’s sophistication allows for a nuanced understanding of the gene-environment interactions, particularly highlighting the role of early-life trauma in shaping lifelong cognitive outcomes. This approach offers a comprehensive framework for analyzing the multifaceted nature of schizophrenia, contributing to a deeper understanding of its etiology and progression.</div></div>","PeriodicalId":55242,"journal":{"name":"Cognitive Systems Research","volume":"88 ","pages":"Article 101288"},"PeriodicalIF":2.1,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142441840","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}

{"title":"Detection of semantic inconsistencies of motor actions: From language to praxis","authors":"Rubén Torres Agustín ,&nbsp;Zareth Bonilla González ,&nbsp;Mario A. Rodríguez Camacho ,&nbsp;Sebastián Almonte ,&nbsp;Wendy Fabiola Lara Galindo ,&nbsp;Francisco Abelardo Robles Aguirre","doi":"10.1016/j.cogsys.2024.101292","DOIUrl":"10.1016/j.cogsys.2024.101292","url":null,"abstract":"<div><div>Semantics of actions includes three types of knowledge: a) of the function of objects and tools, b) of the actions independently of the tools, and c) of the organization of simple actions in sequences. These types of knowledge might be structured as thematic roles into the semantics of actions. To test these hypothesis, 125 illustrations, divided into five conditions: i) Congruent (C), ii) Agent Inconsistent (AI), iii) Instrument Inconsistent (II), iv) Patient Inconsistent (PI), and v) Location Inconsistent (LI), were presented to 23 volunteers (50 % women), aged 20–25, who were asked to respond whether the image was congruent or incongruent. Electrical brain activity was recorded through 20 channels to obtain the event-related potentials (ERP) associated. Lower reaction times for II and PI than C, and a greater number of incorrect trials for C were found. A N300/N400 effect appeared for AI and LI conditions with respect to C. Finally, II and LI conditions present a deflected P600 in reference to C. These findings suggest semantic of actions is sensitive to thematic role manipulations and constitute evidence in favor of a semantic processing shared between visually observed praxis and words.</div></div>","PeriodicalId":55242,"journal":{"name":"Cognitive Systems Research","volume":"88 ","pages":"Article 101292"},"PeriodicalIF":2.1,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142427173","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}

{"title":"What you need to know about a learning robot: Identifying the enabling architecture of complex systems","authors":"Helen Beierling ,&nbsp;Phillip Richter ,&nbsp;Mara Brandt ,&nbsp;Lutz Terfloth ,&nbsp;Carsten Schulte ,&nbsp;Heiko Wersing ,&nbsp;Anna-Lisa Vollmer","doi":"10.1016/j.cogsys.2024.101286","DOIUrl":"10.1016/j.cogsys.2024.101286","url":null,"abstract":"<div><div>Nowadays we deal with robots and AI more and more in our everyday life. However, their behavior is not always apparent to most lay users, especially in error situations. This can lead to misconceptions about the behavior of the technologies being used. This in turn can lead to misuse and rejection by users. Explanation, for example through transparency, can address these misconceptions. However, explaining the entire software or hardware would be confusing and overwhelming for users. Therefore, this paper focuses on the ‘enabling’ architecture. It describes those aspects of a robotic system that may need to be explained to enable someone to use the technology effectively. Furthermore, this paper deals with the ‘explanandum’, i.e. the corresponding misunderstandings or missing concepts of the enabling architecture that need to be clarified. Thus, we have developed and are presenting an approach to determine the ‘enabling’ architecture and the resulting ‘explanandum’ of complex technologies.</div></div>","PeriodicalId":55242,"journal":{"name":"Cognitive Systems Research","volume":"88 ","pages":"Article 101286"},"PeriodicalIF":2.1,"publicationDate":"2024-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142427172","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}

{"title":"A mathematical formulation of learner cognition for personalised learning experiences","authors":"Jeena A. Thankachan,&nbsp;Bama Srinivasan","doi":"10.1016/j.cogsys.2024.101283","DOIUrl":"10.1016/j.cogsys.2024.101283","url":null,"abstract":"<div><div>The paper focuses on the assessment of cognitive skills within Virtual Learning Environments (VLEs). In response to the global shift to remote learning amid the COVID-19 pandemic, VLEs, which include learning management systems (LMS) and online collaboration platforms, gained prominence. The proposed work leverages an established Cattell–Horn–Carroll (CHC) theory to propose eight metrics, which collectively form a part of Cognitive Evaluation Metrics (CEM). The proposed metrics introduce a novel computational approach for multimode evaluation of learners’ cognitive abilities for each learning task within a learning environment. The paper details the formalism for the evaluation of the metrics and makes a contribution towards the potential of the proposed methodology to evaluate cognitive abilities. Additionally, the work implements CEM integration into the learner module of a Game-Based Learning (GBL) environment. Analysis of simulations in the GBL environment, along with statistical analysis, provides insights into the normal distribution of cognitive metrics. This reveals diverse ranges in various abilities such as long or short term memory, working memory, reasoning, attention, and processing speed. The paper also explores the impact of virtual assistants, which highlights their limited relevance to enhance cognitive abilities but serve as valuable on-demand support resources.</div></div>","PeriodicalId":55242,"journal":{"name":"Cognitive Systems Research","volume":"88 ","pages":"Article 101283"},"PeriodicalIF":2.1,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142320388","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}

{"title":"Identification of the emotional component of inner pronunciation: EEG-ERP study","authors":"Ivanov Viacheslav,&nbsp;Vartanov Alexander","doi":"10.1016/j.cogsys.2024.101287","DOIUrl":"10.1016/j.cogsys.2024.101287","url":null,"abstract":"<div><div>The article discusses the problems of identifying the emotional component of inner pronunciation using psychophysiological methods. In the course of preliminary analysis, P200, N400 and LPC were identified, associated with various parameters of prosody regulation during inner pronunciation. An experimental study of inner pronunciation using event-related potentials from EEG was conducted to isolate these components. In addition, a new method of localizing sources of activity using EEG “virtually implanted electrode” was applied in order to study possible sources of the isolated components. The results show the connection of EEG components with various characteristics of prosody (P200 − the beginning of prosody encoding, N400 − the valence of the emotion, LPC − the intensity of the emotion). Based on the results, the participation of various brain structures in the generation of each of the components was also analyzed.</div></div>","PeriodicalId":55242,"journal":{"name":"Cognitive Systems Research","volume":"88 ","pages":"Article 101287"},"PeriodicalIF":2.1,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142323734","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}

{"title":"","authors":"Tianyi Zhang,&nbsp;Jun Tang","doi":"10.1016/j.cogsys.2024.101289","DOIUrl":"10.1016/j.cogsys.2024.101289","url":null,"abstract":"","PeriodicalId":55242,"journal":{"name":"Cognitive Systems Research","volume":"88 ","pages":"Article 101289"},"PeriodicalIF":2.1,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142323735","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}

{"title":"Towards emotion-aware intelligent agents by utilizing knowledge graphs of experiences","authors":"Raziyeh Zall,&nbsp;Mohammad Reza Kangavari","doi":"10.1016/j.cogsys.2024.101285","DOIUrl":"10.1016/j.cogsys.2024.101285","url":null,"abstract":"<div><p>Because of the increasing presence of intelligent agents in various aspects of human social life, social skills play a vital role in ensuring these systems exhibit acceptable and realistic behavior in social communication. The importance of emotional intelligence in social capabilities is noteworthy, so incorporating emotions into the behaviors of intelligent agents is essential. Therefore, some computational models of emotions have been presented to develop intelligent agents that exhibit emotional human-like behaviors. However, most current computational models of emotions neglect the dynamic learning of the affective meaning of events based on agents’ experiences. Such models evaluate the events in the environment according to emotional aspects without considering the context of the situations. Also, these models capture the emotional states of agents by using predefined rules determined according to psychological theories. Therefore, they disregard the data-driven methods that can obtain the relationships between appraisal variables and emotions based on natural human data with fewer assumptions on the nature of such relationships. To address these issues, we proposed a novel and unified affective-cognitive framework (EIAEC) to facilitate the development of emotion-aware intelligent agents. EIAEC uses appraisal theories to acquire the emotional states of the agent in various situations. This paper contains four main contributions: 1- We have designed an efficient episodic memory that uses events and their conditional contexts to store and retrieve knowledge and experiences. This memory facilitates emotional expressions and decision-making adapted to the situations of the agent. 2- A novel method has been proposed that learns context-dependent affective values associated with events by using the agent’s experiences in various contexts. Subsequently, we acquired appraisal variables using the elements and related meta-data in episodic memory. 3- We have proposed a new data-driven method that maps appraisal variables to emotional states. 4- Moreover, a method has been developed to update the activation values regarding actions by using the emotional states of the agent. This method models the influence of emotions on the agent’s decision-making. Finally, we simulate a driving scenarios in our proposed framework to manifest the generated emotions in different situations and conditions. Moreover, we show how the proposed method learns the affective meaning of events and actions used in appraisal computing.</p></div>","PeriodicalId":55242,"journal":{"name":"Cognitive Systems Research","volume":"88 ","pages":"Article 101285"},"PeriodicalIF":2.1,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142239194","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}

{"title":"Exploring the impact of virtual reality flight simulations on EEG neural patterns and task performance","authors":"Evy van Weelden ,&nbsp;Travis J. Wiltshire ,&nbsp;Maryam Alimardani ,&nbsp;Max M. Louwerse","doi":"10.1016/j.cogsys.2024.101282","DOIUrl":"10.1016/j.cogsys.2024.101282","url":null,"abstract":"<div><p>Neurophysiological measurements, such as electroencephalography (EEG), can be used to derive insight into pilots’ mental states during flight training and to track learning progress in order to optimize the training experience for each individual. Prior work has demonstrated that the level of fidelity of a flight simulation (2D Desktop vs. 3D VR) is associated with different cortical activity in relation to task demands. However, it remains unknown whether simulation fidelity affects flight performance, and whether this effect can be observed in EEG neurophysiological responses associated with workload. The current study therefore assessed whether an EEG-based index of workload and task engagement is predictive of performance during flight training in different simulation environments. We conducted a within-subject designed experiment with 53 novice participants who performed two flight tasks (speed change, medium turn) under two conditions (Desktop vs. VR). EEG signals were collected throughout the experiment to quantify mental workload using the beta-ratio (<span><math><mfrac><mi>β</mi><mrow><mi>α</mi><mo>+</mo><mi>θ</mi></mrow></mfrac></math></span>). The VR condition showed increased beta-ratios in all lobes, including frontal and parietal areas, compared to the Desktop simulation. Additionally, we observed an effect of simulator environment on performance, as VR was associated with improved flight performance. However, we found no evidence of a relationship between the beta-ratio and performance. Our findings demonstrate that the brain responds differently to tasks in training environments of various levels of fidelity. However, more research into the neurometrics of flight training is needed in order to develop brain-computer interfaces that can enhance current pilot training methods by providing personalized feedback in real-time.</p></div>","PeriodicalId":55242,"journal":{"name":"Cognitive Systems Research","volume":"88 ","pages":"Article 101282"},"PeriodicalIF":2.1,"publicationDate":"2024-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1389041724000767/pdfft?md5=9f83e22aa6fb4740aa0fce68260eb7b7&pid=1-s2.0-S1389041724000767-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142164457","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}

{"title":"A design for neural network model of continuous reading","authors":"Jarkko Hautala ,&nbsp;Mirka Saarela ,&nbsp;Otto Loberg ,&nbsp;Tommi Kärkkäinen","doi":"10.1016/j.cogsys.2024.101284","DOIUrl":"10.1016/j.cogsys.2024.101284","url":null,"abstract":"<div><p>Cognition and learning are exceedingly modeled as an associative activity of connectionist neural networks. However, only a few such models exist for continuous reading, which involves the delicate coordination of word recognition and eye movements. Moreover, these models are limited to only orthographic level of word processing with predetermined lexicons. Here, we present a conceptual design of a developmentally plausible neural network model of reading designed to simulate word learning, parafoveal preview activation of words, their later foveal word recognition including phonological decoding, and forward saccade length as a control mechanism for intake of new textual information. We will discuss the theoretical advancements of the design and avenues for future developments.</p></div>","PeriodicalId":55242,"journal":{"name":"Cognitive Systems Research","volume":"88 ","pages":"Article 101284"},"PeriodicalIF":2.1,"publicationDate":"2024-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1389041724000780/pdfft?md5=fe87ae81ac59de6166a8de673672c548&pid=1-s2.0-S1389041724000780-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142168016","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}