Biologically Inspired Cognitive Architectures最新文献_第10页

A temporal-causal network model for the effect of emotional charge on information sharing 情绪负荷对信息共享影响的时间-因果网络模型

Biologically Inspired Cognitive Architectures Pub Date : 2018-10-01 DOI: 10.1016/j.bica.2018.10.003

Rosa Schoenmaker, Jan Treur, Boaz Vetter

引用次数: 4

A bio-inspired self-responding emotional behavior system for virtual creatures 虚拟生物的仿生自我反应情感行为系统

Biologically Inspired Cognitive Architectures Pub Date : 2018-10-01 DOI: 10.1016/j.bica.2018.07.012

Diana G. Gómez-Martínez , Jonathan-Hernando Rosales , Vianney Muñoz-Jiménez , Félix Ramos , Marco Ramos

引用次数: 4

A computational model of empathy for interactive agents 交互式代理的共情计算模型

Biologically Inspired Cognitive Architectures Pub Date : 2018-10-01 DOI: 10.1016/j.bica.2018.07.010

Ӧzge Nilay Yalcin, Steve DiPaola

引用次数: 53

Multi-level metacognition for adaptive behavior 适应性行为的多层次元认知

Biologically Inspired Cognitive Architectures Pub Date : 2018-10-01 DOI: 10.1016/j.bica.2018.10.006

Marvin Conn , Kenneth M'Bale , Darsana Josyula

{"title":"Multi-level metacognition for adaptive behavior","authors":"Marvin Conn , Kenneth M'Bale , Darsana Josyula","doi":"10.1016/j.bica.2018.10.006","DOIUrl":"10.1016/j.bica.2018.10.006","url":null,"abstract":"<div><p><span>Behavior<span> adaptation is an integral aspect for autonomous agents to survive in a world where change is normal. Animals change their foraging routines and socializing habits based on predator risks in their environment. Humans adapt their behavior based on current interests, social norms, stress level, health conditions, upcoming deadlines and various other factors. Artificial agents need to effectively adapt to changes in their environment such that they can quickly adjust their behavior to maintain performance in the changed environment. In this paper, we present a multi-level metacognitive model that allows agents to adapt their behavior in various ways based on the resources available for metacognitive processing. As the agent operates at higher levels of this model, the agent is better equipped to adapt to a wider range of changes. The model has been tested on 2 different applications: (i) a reinforcement learner-based agent trying to navigate and collect rewards in a seasonal grid-world environment and (ii) a convolutional neural network-based agent trying to classify the signals in a </span></span>radio frequency spectrum world and separate them into known modulations and unknown modulations.</p></div>","PeriodicalId":48756,"journal":{"name":"Biologically Inspired Cognitive Architectures","volume":"26 ","pages":"Pages 174-183"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.bica.2018.10.006","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48533927","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Brain computer interface: A comprehensive survey 脑机接口:综合调查

Biologically Inspired Cognitive Architectures Pub Date : 2018-10-01 DOI: 10.1016/j.bica.2018.10.005

Neha Tiwari, Damodar Reddy Edla, Shubham Dodia, Annushree Bablani

{"title":"Brain computer interface: A comprehensive survey","authors":"Neha Tiwari, Damodar Reddy Edla, Shubham Dodia, Annushree Bablani","doi":"10.1016/j.bica.2018.10.005","DOIUrl":"10.1016/j.bica.2018.10.005","url":null,"abstract":"<div><p><span>The contemporary era demands a progress with respect to manual work or even semi-machine dependence and the desired procession can be provided by Brain Computer Interface (BCI). As the name suggests, BCI is a bridge between the signals that are generated by the thoughts in our brain and the machine that can implement the produced signals into actions. It is a breakthrough invention in the field of brain-mapping science which can adequately help and aid impaired vision, movement, </span>hearing and any damaged functioning of the body that can be thought of as practically. In this paper, a comprehensive survey on the evolution of BCI with a basic introduction of the functioning of the brain has been provided. A detailed extensive revision on the structure of human brain, BCI and its phases, the mechanisms to extract the signals and the algorithms to put the extracted information to use is provided throughout the course of this study. A comparative study of the phases followed by an extensive discussion of the benchmark techniques has been given. The various bottlenecks have been identified and it has been reasoned why most BCI systems remain as mere prototypes. The ongoing research and progress in the field have been studied and detailed in this review.</p></div>","PeriodicalId":48756,"journal":{"name":"Biologically Inspired Cognitive Architectures","volume":"26 ","pages":"Pages 118-129"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.bica.2018.10.005","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49285826","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 43

CIT: Integrated cognitive computing and cognitive agent technologies based cognitive architecture for human-like functionality in artificial systems CIT:基于人工系统中类人功能的认知架构的集成认知计算和认知代理技术

Biologically Inspired Cognitive Architectures Pub Date : 2018-10-01 DOI: 10.1016/j.bica.2018.07.020

A. Chandiok , D.K. Chaturvedi

{"title":"CIT: Integrated cognitive computing and cognitive agent technologies based cognitive architecture for human-like functionality in artificial systems","authors":"A. Chandiok , D.K. Chaturvedi","doi":"10.1016/j.bica.2018.07.020","DOIUrl":"10.1016/j.bica.2018.07.020","url":null,"abstract":"<div><p><span>The paper proposes a novel cognitive architecture that combines cognitive computing and cognitive agent technologies for performing human-like functionality. The system architecture<span><span><span> is known as CIT (Cognitive Information Technology). This design takes advantage of cognitive computing to handle Experiential Information (EI) using audio processing, </span>computer vision, </span>natural language processing<span><span><span>, text mining, and data mining techniques. The </span>CIT architecture includes human like cognitive agent functionality comprising attention, learning, memory, action selection, and action to handle human like individual and distributed knowledge bases to create rational decisions. The work shows CIT architecture practical implementation through “CIT framework” developed in C# and </span>python language. For validating the system performance, the paper shows </span></span></span><span><em>CIT based Object Recognition and </em><em>Question Answering System</em></span>. This framework is anticipated to advance the quality of artificial intelligent agent based decision-making using human like perception, comprehend and action skills, reducing real world business errors and assuring the correct, accurate, knowledgeable and well-timed human like decisions.</p></div>","PeriodicalId":48756,"journal":{"name":"Biologically Inspired Cognitive Architectures","volume":"26 ","pages":"Pages 55-79"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.bica.2018.07.020","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44722476","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 10

An urban traffic controller using the MECA cognitive architecture 使用MECA认知架构的城市交通控制器

Biologically Inspired Cognitive Architectures Pub Date : 2018-10-01 DOI: 10.1016/j.bica.2018.07.015

Ricardo Gudwin , André Paraense , Suelen M. de Paula , Eduardo Fróes , Wandemberg Gibaut , Elisa Castro , Vera Figueiredo , Klaus Raizer

{"title":"An urban traffic controller using the MECA cognitive architecture","authors":"Ricardo Gudwin , André Paraense , Suelen M. de Paula , Eduardo Fróes , Wandemberg Gibaut , Elisa Castro , Vera Figueiredo , Klaus Raizer","doi":"10.1016/j.bica.2018.07.015","DOIUrl":"10.1016/j.bica.2018.07.015","url":null,"abstract":"<div><p>In this paper, we present a Cognitive Manager for urban traffic control, built using MECA, the Multipurpose Enhanced Cognitive Architecture, a cognitive architecture developed by our research group and implemented in the Java language. The Cognitive Manager controls a set of traffic lights in a junction of roads based on information collected from sensors installed on the many lanes feeding the junction. We tested our Junction Manager in 4 different test topologies using the SUMO traffic simulator, and with different traffic loads. The junction manager seeks to optimize the average waiting times for all the cars crossing the junction, while at the same time being able to provide preference to special cars (police cars or firefighters), called Smart Cars, and equipped with special devices that grant them special treatment during the phase allocation policies provided by the architecture. Simulation results provide evidence for an enhanced behavior while compared to fixed-time policies.</p></div>","PeriodicalId":48756,"journal":{"name":"Biologically Inspired Cognitive Architectures","volume":"26 ","pages":"Pages 41-54"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.bica.2018.07.015","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44765915","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

An adaptive network model for a possible therapy for the effects of a certain type of dementia on social functioning 一个自适应网络模型，可能治疗某种类型的痴呆症对社会功能的影响

Biologically Inspired Cognitive Architectures Pub Date : 2018-10-01 DOI: 10.1016/j.bica.2018.10.002

Charlotte Commu , Jan Treur , Annemieke Dols , Yolande A.L. Pijnenburg

引用次数: 0

Network Modeling Environment for Supporting Families of Displaced Concepts 支持置换概念族的网络建模环境

Biologically Inspired Cognitive Architectures Pub Date : 2018-08-22 DOI: 10.1007/978-3-319-99316-4_25

S. Kosikov, L. Ismailova, Viacheslav Wolfengagen

引用次数: 3

Analysis of Gaze Behaviors in Virtual Environments for Cooperative Pattern Modeling 基于协同模式建模的虚拟环境凝视行为分析

Biologically Inspired Cognitive Architectures Pub Date : 2018-08-22 DOI: 10.1007/978-3-319-99316-4_43

Norifumi Watanabe, Kota Itoda

引用次数: 0