Cognitive Learning Methodologies for Brain-Inspired Cognitive Robotics

Author(s):  
Yingxu Wang

Cognitive robots are brain-inspired robots that are capable of inference, perception, and learning mimicking the cognitive mechanisms of the brain. Cognitive learning theories and methodologies for knowledge and behavior acquisition are centric in cognitive robotics. This paper explores the cognitive foundations and denotational mathematical means of cognitive learning engines (CLE) and cognitive knowledge bases (CKB) for cognitive robots. The architectures and functions of CLE are formally presented. A content-addressed knowledge base access methodology for CKB is rigorously elaborated. The CLE and CKB methodologies are not only designed to explain the mechanisms of human knowledge acquisition and learning, but also applied in the development of cognitive robots, cognitive computers, and knowledge-based systems.

Author(s):  
Yingxu Wang

A cognitive knowledge base (CKB) is a novel structure of intelligent knowledge base that represents and manipulates knowledge as a dynamic concept network mimicking human knowledge processing. The essence of CKB is the denotational mathematical model of formal concept that is dynamically associated to other concepts in a CKB beyond conventional rule-based or ontology-based knowledge bases. This paper presents a formal CKB and autonomous knowledge manipulation system based on recent advances in neuroinformatics, concept algebra, semantic algebra, and cognitive computing. An item knowledge in CKB is represented by a formal concept, while the entire knowledge base is embodied by a dynamic concept network. The CKB system is manipulated by algorithms of knowledge acquisition and retrieval on the basis of concept algebra. CKB serves as a kernel of cognitive learning engines for cognitive robots and machine learning systems. CKB plays a central role not only in explaining the mechanisms of human knowledge acquisition and learning, but also in the development of cognitive robots, cognitive learning engines, and knowledge-based systems.


Author(s):  
Yingxu Wang ◽  
Yousheng Tian

Intelligent knowledge base theories and technologies are fundamentally centric in machine learning and cognitive robotics. This paper presents the design of a formal knowledge retrieval system (FKTS) for intelligent knowledge base modeling and manipulations based on concept algebra. In order to rigorously design and implement FKTS, real-time process algebra (RTPA) is adopted to formally describe the architectures and behaviors of FKTS. The architectural model of FKTS in the form of a set of unified structure models (USMs) is rigorously described. On the basis of USMs, functional models of FKTS are hierarchically refined by a set of unified process models (UPMs). The UPMs of FFTS are divided into two subsystems known as those of the knowledge visualization and knowledge base retrieval subsystems where the content-addressed searching mechanism is implemented in knowledge bases manipulations. The FKTS system is design and implemented as a part of the cognitive learning engine (CLE) for cognitive computers and cognitive robots.


Author(s):  
Alessandro Di Nuovo ◽  
Angelo Cangelosi

Abstract Purpose of Review Understanding and manipulating abstract concepts is a fundamental characteristic of human intelligence that is currently missing in artificial agents. Without it, the ability of these robots to interact socially with humans while performing their tasks would be hindered. However, what is needed to empower our robots with such a capability? In this article, we discuss some recent attempts on cognitive robot modeling of these concepts underpinned by some neurophysiological principles. Recent Findings For advanced learning of abstract concepts, an artificial agent needs a (robotic) body, because abstract and concrete concepts are considered a continuum, and abstract concepts can be learned by linking them to concrete embodied perceptions. Pioneering studies provided valuable information about the simulation of artificial learning and demonstrated the value of the cognitive robotics approach to study aspects of abstract cognition. Summary There are a few successful examples of cognitive models of abstract knowledge based on connectionist and probabilistic modeling techniques. However, the modeling of abstract concept learning in robots is currently limited at narrow tasks. To make further progress, we argue that closer collaboration among multiple disciplines is required to share expertise and co-design future studies. Particularly important is to create and share benchmark datasets of human learning behavior.


Author(s):  
Peter R. Monge ◽  
Noshir Contractor

This chapter reviews theory and research that seeks to explain the emergence of communication networks based on individuals’ cognitions about other people and the relations among those individuals. Contagion theories seek to explain networks as conduits for “infectious” attitudes and behavior. Semantic theories attempt explanations on the basis of networks that map similarities among individuals’ interpretations. Theories of cognitive social structures examine cognitions regarding “who knows who” and “who knows who knows who,” while theories of cognitive knowledge structures examine cognitions of “who knows what” and “who knows who knows what.” Finally, cognitive consistency theories explain how networks are understood on the basis of individuals’ cognitions of consistency or balance in their networks. The remainder of this chapter discusses each of these areas and their extensions. Contagion theories are based on the assumption that the opportunities for contact provided by communication networks serve as a mechanism that exposes people, groups, and organizations to information, attitudinal messages, and the behavior of others (Burt, 1980, 1987; Contractor & Eisenberg, 1990). This exposure increases the likelihood that network members will develop beliefs, assumptions, and attitudes that are similar to those of others in their network (Carley, 1991; Carley & Kaufer, 1993). The contagion approach seeks to explain organizational members’ knowledge, attitudes, and behavior on the basis of information, attitudes, and behavior of others in the network to whom they are linked. Rogers and Kincaid (1981) refer to this as the convergence model of communication. Theories that are premised on a contagion model, at least in part, include social information processing theory (Fulk, Steinfield, Schmitz, & Power, 1987; Salancik & Pfeffer, 1978), social influence theory (Fulk, Schmitz, & Steinfield, 1990; see also Marsden & Friedkin, 1993), structural theory of action (Burt, 1982), symbolic interactionist perspectives (Trevino, Lengel, & Daft, 1987), mimetic processes exemplified by institutional theories (DiMaggio & Powell, 1983; Meyer & Rowan, 1977), and social cognitive and learning theories (Bandura, 1986). Fulk (1993) notes that these constructivist perspectives “share the core proposition that social and symbolic processes produce patterns of shared cognitions and behaviors that arise from forces well beyond the demands of the straightforward task of information processing in organizations”.


2013 ◽  
Vol 1 (1) ◽  
pp. 158-178
Author(s):  
Urcun John Tanik

Cyberphysical system design automation utilizing knowledge based engineering techniques with globally networked knowledge bases can tremendously improve the design process for emerging systems. Our goal is to develop a comprehensive architectural framework to improve the design process for cyberphysical systems (CPS) and implement a case study with Axiomatic Design Solutions Inc. to develop next generation toolsets utilizing knowledge-based engineering (KBE) systems adapted to multiple domains in the field of CPS design automation. The Cyberphysical System Design Automation Framework (CPSDAF) will be based on advances in CPS design theory based on current research and knowledge collected from global sources automatically via Semantic Web Services. A case study utilizing STEM students is discussed.


2021 ◽  
Vol 31 (Supplement_3) ◽  
Author(s):  
S Tzvetkova ◽  
N Tschilingirova

Abstract Background Theoretically there are several insufficiently confirmed statements based on evidences that underline the important role of psychological assistance to patients with malignant neoplasms. Since April, 2021, Mental Adjustment to Cancer Scale (MAC) is translated into Bulgarian and it was introduced to psycho-oncologic practice in Bulgaria. Methods The concise variant of MAC - Mini Mental Adjustment to Cancer Scale (Mini-MAC) has been implemented evaluating the degree when the patients perceive their adaptation to the diagnosis and cancer treatment. It comprises 29 items and measures four inner scales: determination, helplessness, anxiety, cognitive negligence and fatalism. It has been applied in compliance with strict confidentiality, voluntary principle and objectivity to 30 patients - 14 male and 16 female. Results MAC scales have good consistency - alpha coefficient from 0.56 to 0.74. The age correlates moderately with disease type (r=.35, p = 0.05). Helplessness is in positive relation to anxiety (r=.63, p = 0.000) and fatalism (r=.30, p = 0.05), and in negative one to determination (r=-.35, p = 0.05). The determination is in statistic positive relation to cognitive negligence (r=.44, p = 0.02). Conclusions The malignant disease type does not influence the scale results. They are influenced by inner factors as morbid experience, sensitivity to the disease, psychological protections that are frequently demonstrated by cognitive negligence and determination. MAC has been successfully implemented in the clinical psychological counseling in Bulgaria. Key messages Mental Adjustment to Cancer Scale identifies patients' adaptation to cancer and is introduced in Bulgaria. The methodology shows the established cognitive mechanisms for personal understanding and behavior in the course of treatment.


2017 ◽  
Vol 6 (2) ◽  
pp. 33
Author(s):  
Akhmad Pandu Setiawan

Behaviorism learning theory is oriented towards results that can be measured and observed. Repetition and training used so that the desired behavior can become a habit. The expected results of the implementation of this behavioristic theory is the formation of a desired behavior. The desirable behavior gets positive reinforcement and behavior that is not appropriate awarded the negative. Evaluation or assessment based on observed behavior. In theory this learned professor was not much give a lecture, but the brief instruction is followed by examples by themselves or through simulation. The purpose of this paper is to describe the application of the theory Behavioristic and konstruktifistik in learning activities at the School of Raden Wijaya Tarbiyah Mojokerto. Behavioristic learning theory emphasizes the changes in behavior as well as a result of the interaction between stimulus and response. Learning is a process of behavioral changes as a result of the interaction between stimulus and response. A person is considered to have learned if he could show changes in behavior. Although learning theory tigkah behavior began to be abandoned century, but collaborate on this theory with cognitive learning theory and the theory of other learning is essential for creating a learning approach that is appropriate and effective, because basically there is no single theory of learning that is truly suited to creating a learning approaches and effective fit. especially with constructivism learning model. The role of the faculty in constructivist learning very demanding mastery of a broad and in-depth about the material taught. A broad and deep knowledge allow a lecturer accept different views and ideas of students and also makes it possible to indicate whether or not the idea of ​​the road. Mastery of the material allows a professor to understand all kinds of roads and the model to arrive at a solution to the problem without fixed on one model.


Author(s):  
A. L. Semenov ◽  
V. I. Ershov ◽  
D. A. Gusarov

This paper deals with the concept of the translation approach to the problem of interaction of language and culture in terms of determination of the translation solutions by linguoethnic factors. The authors pay main attention to the analysis of the notion of culture. The concept proceeds from the views and opinions regarding the culture and its role in shaping the identity of the person introduced by the honorary doctor (doctor honoris cause) of the MGIMO-University Federico Major in his book «New page». Sharing the point of view of F. Major , the authors come to the conclusion that culture is a knowledge, based on which an individual perceives and evaluates his performance and behavior. Projecting such a position on the verbal behavior, the authors highlight the leading role of culture in the process of producing a speech act played when choosing the individual models of behavior on the basis of the knowledge of the communicative situation. Based on F. Mayor`s opinion that culture unites rather than divides people, the authors note the presence of universal and unique linguoethnic elements in the cultural knowledge of the representatives of various ethnic groups which determine the degree of similarities and differences in the ways of expressing knowledge in different languages. In this paper the authors reasonably use the term «linguoethnic» to describe the cultural-cognitive peculiarities inherent to individuals as representatives of different ethnic groups, as well as give comparison of the terms «linguoethnic» and «linguocultural».


Author(s):  
Kun Sun ◽  
Boi Faltings

Abstract Knowledge-based CAD systems limit designers’ creativity by constraining them to work with the prototypes provided by the systems’ knowledge bases. We investigate knowledge-based CAD systems capable of supporting creative designs in the example domain of elementary mechanisms. We present a technique based on qualitative explanations which allows a designer to extend the knowledge base by demonstrating a structure which implements a function in a creative way. Structure is defined as the geometry of the parts, and function using a general logical language based on qualitative physics. We argue that the technique can accommodate any creative design in the example domain, and we demonstrate the technique using an example of a creative design. The use of qualitative physics as a tool for extensible knowledge-based systems points out a new and promising application area for qualitative physics.


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