scholarly journals Preface: A Forum at the Dawn of the Era of Biologically Inspired Intelligent Machines

2014 ◽  
Vol 41 ◽  
pp. 1-5
Author(s):  
Alexei V. Samsonovich ◽  
Paul Robertson
Keyword(s):  
Biologically Inspired ◽  
Intelligent Machines

Research on Human Cognition for Biologically Inspired Developments

2017 ◽  
pp. 83-116 ◽  
Author(s):  
Marko Wehle ◽  
Alexandra Weidemann ◽  
Ivo Wilhelm Boblan
Keyword(s):  
Role Model ◽  
Cognitive Model ◽  
Human Robot Interaction ◽  
Human Cognition ◽  
Biologically Inspired ◽  
Robot Interaction ◽  
Intelligent Machines ◽  
The World ◽  
Conducting Research ◽  
Interaction Research

Robotic developments are seen as a next level in technology with intelligent machines, which automate tedious tasks and serve our needs without complaints. But nevertheless, they have to be fair and smart enough to be intuitively of use and safe to handle. But how to implement this kind of intelligence, does it need feelings and emotions, should robots perceive the world as we do as a human role model, how far should the implementation of synthetic consciousness lead and actually, what is needed for consciousness in that context? Additionally in Human-Robot-Interaction research, science mainly makes use of the tool phenomenography, which is exclusively subjective, so how to make it qualify for Artificial Intelligence? These are the heading aspects of this chapter for conducting research in the field of social robotics and suggesting a conscious and cognitive model for smart and intuitive interacting robots, guided by biomimetics.

Research on Human Cognition for Biologically Inspired Developments

2020 ◽  
pp. 1507-1532
Author(s):  
Marko Wehle ◽  
Alexandra Weidemann ◽  
Ivo Wilhelm Boblan
Keyword(s):  
Role Model ◽  
Cognitive Model ◽  
Human Robot Interaction ◽  
Human Cognition ◽  
Biologically Inspired ◽  
Robot Interaction ◽  
Intelligent Machines ◽  
The World ◽  
Conducting Research ◽  
Interaction Research

Robotic developments are seen as a next level in technology with intelligent machines, which automate tedious tasks and serve our needs without complaints. But nevertheless, they have to be fair and smart enough to be intuitively of use and safe to handle. But how to implement this kind of intelligence, does it need feelings and emotions, should robots perceive the world as we do as a human role model, how far should the implementation of synthetic consciousness lead and actually, what is needed for consciousness in that context? Additionally in Human-Robot-Interaction research, science mainly makes use of the tool phenomenography, which is exclusively subjective, so how to make it qualify for Artificial Intelligence? These are the heading aspects of this chapter for conducting research in the field of social robotics and suggesting a conscious and cognitive model for smart and intuitive interacting robots, guided by biomimetics.

Biomimetics and the Evolution of Robotics and Intelligent Systems

2018 ◽  
pp. 1-25
Author(s):  
Maki K. Habib ◽  
Fusaomi Nagata
Keyword(s):  
Intelligent Systems ◽  
Research Field ◽  
Biologically Inspired ◽  
Intelligent Machines ◽  
Interdisciplinary Field ◽  
Research Activities ◽  
Engineering Sciences ◽  
Application Potential ◽  
Design Ideas ◽  
Scientific Ideas

Biologically inspired systems, known as “biomimetics” or the “mimicry of nature,” is an interdisciplinary scientific research field inspired by nature and featured by the technology outcome (hardware and software) and lies at the interface of biology, physics, chemistry, information, and engineering sciences. Biomimetics is initiated by making nature a model of inspiration that would immensely help conscious abstraction of new innovative principles and creative design ideas and concepts that help developing new techniques and functionalities, seeking new paradigms and methods, designing new materials, and developing new streams of intelligent machines, robots, systems, devices, algorithms, etc. Biologically inspired approaches create a new reality with great development and application potential with the goal of identifying specific desirable qualities and attributes in biological systems and using them in the design of new products and systems. This chapter provides the importance of biomimetic as an interdisciplinary field and its evolution, advances, challenges, and constraints along with the associated enabling technologies supporting its growth. In addition, it introduces scientific ideas and directions of research activities in the field. The chapter also presents key developments in the field of biomimetic robots and underlines the challenges facing it.

scholarly journals Performance vs. competence in human–machine comparisons

2020 ◽  
Vol 117 (43) ◽  
pp. 26562-26571 ◽  
Author(s):  
Chaz Firestone
Keyword(s):  
Systems Approach ◽  
Brain Activity ◽  
Human Mind ◽  
Learning Systems ◽  
Behavioral Differences ◽  
Biologically Inspired ◽  
Playing Field ◽  
Intelligent Machines ◽  
The World ◽  
Exciting Possibility

Does the human mind resemble the machines that can behave like it? Biologically inspired machine-learning systems approach “human-level” accuracy in an astounding variety of domains, and even predict human brain activity—raising the exciting possibility that such systems represent the world like we do. However, even seemingly intelligent machines fail in strange and “unhumanlike” ways, threatening their status as models of our minds. How can we know when human–machine behavioral differences reflect deep disparities in their underlying capacities, vs. when such failures are only superficial or peripheral? This article draws on a foundational insight from cognitive science—the distinction between performance and competence—to encourage “species-fair” comparisons between humans and machines. The performance/competence distinction urges us to consider whether the failure of a system to behave as ideally hypothesized, or the failure of one creature to behave like another, arises not because the system lacks the relevant knowledge or internal capacities (“competence”), but instead because of superficial constraints on demonstrating that knowledge (“performance”). I argue that this distinction has been neglected by research comparing human and machine behavior, and that it should be essential to any such comparison. Focusing on the domain of image classification, I identify three factors contributing to the species-fairness of human–machine comparisons, extracted from recent work that equates such constraints. Species-fair comparisons level the playing field between natural and artificial intelligence, so that we can separate more superficial differences from those that may be deep and enduring.

THE CONCEPT OF AUTONOMOUS SYSTEMS IN INDUSTRY 4.0

2019 ◽  
Vol 12 (1) ◽  
pp. 77-87
Author(s):  
György Kovács ◽  
Rabab Benotsmane ◽  
László Dudás
Keyword(s):  
Industry 4.0 ◽  
Intelligent Systems ◽  
Autonomous Systems ◽  
Essential Element ◽  
Industrial Sector ◽  
Life Cycles ◽  
Multi Agent Systems ◽  
New Paradigm ◽  
Intelligent Machines ◽  
Digital Network

Recent tendencies – such as the life-cycles of products are shorter while consumers require more complex and more unique final products – poses many challenges to the production. The industrial sector is going through a paradigm shift. The traditional centrally controlled production processes will be replaced by decentralized control, which is built on the self-regulating ability of intelligent machines, products and workpieces that communicate with each other continuously. This new paradigm known as Industry 4.0. This conception is the introduction of digital network-linked intelligent systems, in which machines and products will communicate to one another in order to establish smart factories in which self-regulating production will be established. In this article, at first the essence, main goals and basic elements of Industry 4.0 conception is described. After it the autonomous systems are introduced which are based on multi agent systems. These systems include the collaborating robots via artificial intelligence which is an essential element of Industry 4.0.

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