Conferences related to Animal behavior

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2019 9th International IEEE/EMBS Conference on Neural Engineering (NER)

Neural Engineering

  • 2017 8th International IEEE/EMBS Conference on Neural Engineering (NER)

    Neural Engineering is an emerging core discipline,which coalesces neuroscience with engineering.Members of both the Neuroscience and Engineering Communities areencouraged to attend this highly multidisciplinarymeeting. The conference will highlight the emergingengineering innovations in the restoration andenhancement of impaired sensory, motor, andcognitive functions, novel engineering for deepeningknowledge of brain function, and advanced designand use of neurotechnologies

  • 2015 7th International IEEE/EMBS Conference on Neural Engineering (NER)

    Neural engineering deals with many aspects of basic and clinical problemsassociated with neural dysfunction including the representation of sensory and motor information, theelectrical stimulation of the neuromuscular system to control the muscle activation and movement, theanalysis and visualization of complex neural systems at multi -scale from the single -cell and to the systemlevels to understand the underlying mechanisms, the development of novel neural prostheses, implantsand wearable devices to restore and enhance the impaired sensory and motor systems and functions.

  • 2013 6th International IEEE/EMBS Conference on Neural Engineering (NER)

    Neural engineering deals with many aspects of basic and clinical problems associated with neural dysfunction including the representation of sensory and motor information, the electrical stimulation of the neuromuscular system to control the muscle activation and movement, the analysis and visualization of complex neural systems at multi-scale from the single-cell and to the system levels to understand the underlying mechanisms, the development of novel neural prostheses, implants and wearable devices to restore and enhance the impaired sensory and motor systems and functions.

  • 2011 5th International IEEE/EMBS Conference on Neural Engineering (NER)

    highlight the emerging field, Neural Engineering that unites engineering, physics, chemistry, mathematics, computer science with molecular, cellular, cognitive and behavioral neuroscience and encompasses such areas as replacing or restoring lost sensory and motor abilities, defining the organizing principles and underlying mechanisms of neural systems, neurorobotics, neuroelectronics, brain imaging and mapping, cognitive science and neuroscience.

  • 2009 4th International IEEE/EMBS Conference on Neural Engineering (NER)

    highlight the emerging field, Neural Engineering that unites engineering, physics, chemistry, mathematics, computer science with molecular, cellular, cognitive and behavioral neuroscience and encompasses such areas as replacing or restoring lost sensory and motor abilities, defining the organizing principles and underlying mechanisms of neural systems, neurorobotics, neuroelectronics, brain imaging and mapping, cognitive science and neuroscience.

  • 2007 3rd International IEEE/EMBS Conference on Neural Engineering

  • 2005 2nd International IEEE/EMBS Conference on Neural Engineering

  • 2003 1st International IEEE/EMBS Conference on Neural Engineering


2019 IEEE Underwater Technology (UT)

The symposium scope is to provide a thematic umbrella for researchers working in underwater systems across the world to discuss the problems and potential long-term solutions that concern not only the Asian countries, but the world ocean in general.


2018 13th ACM/IEEE International Conference on Human-Robot Interaction (HRI)

HRI is a highly selective annual conference that showcases the very best research and thinking in human-robot interaction. HRI is inherently interdisciplinary and multidisciplinary, reflecting work from researchersin robotics, psychology, cognitive science, HCI, human factors, artificial intelligence, organizational behavior,anthropology, and many other fields.

  • 2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI)

    HRI is a highly selective annual conference that showcases the very best research and thinking in human-robot interaction. HRI is inherently interdisciplinary and multidisciplinary, reflecting work from researchers in robotics, psychology, cognitive science, HCI, human factors, artificial intelligence, organizational behavior, anthropology, and many other fields.

  • 2017 12th ACM/IEEE International Conference on Human-Robot Interaction (HRI)

    The conference serves as the primary annual meeting for researchers in the field of human-robot interaction. The event will include a main papers track and additional sessions for posters, demos, and exhibits. Additionally, the conference program will include a full day of workshops and tutorials running in parallel.

  • 2016 11th ACM/IEEE International Conference on Human-Robot Interaction (HRI)

    This conference focuses on the interaction between humans and robots.

  • 2015 10th ACM/IEEE International Conference on Human-Robot Interaction (HRI)

    HRI is a single -track, highly selective annual conference that showcases the very bestresearch and thinking in human -robot interaction. HRI is inherently interdisciplinary and multidisciplinary,reflecting work from researchers in robotics, psychology, cognitive science, HCI, human factors, artificialintelligence, organizational behavior, anthropology, and many other fields.

  • 2014 9th ACM/IEEE International Conference on Human-Robot Interaction (HRI)

    HRI is a highly selective annual conference that showcases the very best research and thinking in human -robot interaction. HRI is inherently interdisciplinary and multidisciplinary, reflecting work from researchers in robotics, psychology, cognitive science, HCI, human factors, artificial intelligence, organizational behavior, anthropology, and many other fields.

  • 2013 8th ACM/IEEE International Conference on Human-Robot Interaction (HRI)

    HRI is a single -track, highly selective annual conference that showcases the very best research and thinking in human-robot interaction. HRI is inherently interdisciplinary and multidisciplinary, reflecting work from researchers in robotics, psychology, cognitive science, HCI, human factors, artificial intelligence, organizational behavior, anthropology, and many other fields.

  • 2012 7th ACM/IEEE International Conference on Human-Robot Interaction (HRI)

    HRI is a single-track, highly selective annual conference that showcases the very best research and thinking in human-robot interaction. HRI is inherently interdisciplinary and multidisciplinary, reflecting work from researchers in robotics, psychology, cognitive science, HCI, human factors, artificial intelligence, organizational behavior, anthropology, and many other fields.

  • 2011 6th ACM/IEEE International Conference on Human-Robot Interaction (HRI)

    Robot companions Lifelike robots Assistive (health & personal care) robotics Remote robots Mixed initiative interaction Multi-modal interaction Long-term interaction with robots Awareness and monitoring of humans Task allocation and coordination Autonomy and trust Robot-team learning User studies of HRI Experiments on HRI collaboration Ethnography and field studies HRI software architectures HRI foundations Metrics for teamwork HRI group dynamics.

  • 2010 5th ACM/IEEE International Conference on Human-Robot Interaction (HRI)

    TOPICS: Robot companions, Lifelike robots, Assistive (health & personal care) robotics, Remote robots, Mixed initiative interaction, Multi-modal interaction, Long-term interaction with robots, Awareness and monitoring of humans, Task allocation and coordination, Autonomy and trust, Robot-team learning, User studies of HRI, Experiments on HRI collaboration, Ethnography and field studies, HRI software architectures

  • 2009 4th ACM/IEEE International Conference on Human-Robot Interaction (HRI)

    * Robot companions * Lifelike robots * Assistive (health & personal care) robotics * Remote robots * Mixed initiative interaction * Multi-modal interaction * Long-term interaction with robots * Awareness and monitoring of humans * Task allocation and coordination * Autonomy and trust * Robot-team learning * User studies of HRI * Experiments on HRI collaboration * Ethnography and field studies * HRI software architectures

  • 2008 3rd ACM/IEEE International Conference on Human-Robot Interaction (HRI)

    Robot companions Lifelike robots Assistive (health & personal care) robotics Remote robots Mixed initiative interaction Multi-modal interaction Long-term interaction with robots Awareness and monitoring of humans Task allocation and coordination Autonomy and trust Robot-team learning User studies of HRI Experiments on HRI collaboration Ethnography and field studies HRI software architectures HRI foundations Metrics for teamwork HRI group dynamics Individual vs. group HRI

  • 2007 2nd Annual Conference on Human-Robot Interaction (HRI)


2018 14th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications (MESA)

The goal of the 14th ASME/IEEE MESA2018 is to bring together experts from the fields of mechatronic and embedded systems, disseminate the recent advances in the area, discuss future research directions, and exchange application experience. The main achievement of MESA2018 is to bring out and highlight the latest research results and developments in the IoT (Internet of Things) era in the field of mechatronics and embedded systems.


2018 15th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON)

The 15th annual IEEE SECON conference will provide a unique forum to exchange innovative research ideas, recent results, and share experiences among researchers and practitioners in wireless networks, mobile systems and the Internet of Things. The focus of IEEE SECON is novel communication technologies and emerging applications and services, involving mobile sensing and communication, and ubiquitous and pervasive computing.


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Periodicals related to Animal behavior

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Automatic Control, IEEE Transactions on

The theory, design and application of Control Systems. It shall encompass components, and the integration of these components, as are necessary for the construction of such systems. The word `systems' as used herein shall be interpreted to include physical, biological, organizational and other entities and combinations thereof, which can be represented through a mathematical symbolism. The Field of Interest: shall ...


Biomedical Circuits and Systems, IEEE Transactions on

The Transactions on Biomedical Circuits and Systems addresses areas at the crossroads of Circuits and Systems and Life Sciences. The main emphasis is on microelectronic issues in a wide range of applications found in life sciences, physical sciences and engineering. The primary goal of the journal is to bridge the unique scientific and technical activities of the Circuits and Systems ...


Biomedical Engineering, IEEE Transactions on

Broad coverage of concepts and methods of the physical and engineering sciences applied in biology and medicine, ranging from formalized mathematical theory through experimental science and technological development to practical clinical applications.


Circuits and Systems Magazine, IEEE


Computational Biology and Bioinformatics, IEEE/ACM Transactions on

Specific topics of interest include, but are not limited to, sequence analysis, comparison and alignment methods; motif, gene and signal recognition; molecular evolution; phylogenetics and phylogenomics; determination or prediction of the structure of RNA and Protein in two and three dimensions; DNA twisting and folding; gene expression and gene regulatory networks; deduction of metabolic pathways; micro-array design and analysis; proteomics; ...


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Most published Xplore authors for Animal behavior

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Xplore Articles related to Animal behavior

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Practical Stability Analysis for Exponential Type Stochastic Swarms

[{u'author_order': 1, u'full_name': u'Zhibin Xue'}, {u'author_order': 2, u'full_name': u'Jianchao Zeng'}] 2009 International Conference on Computational Intelligence and Software Engineering, 2009

A novel Lagrangian "individual-based" isotropic continuous time exponential type stochastic swarming model in an n-dimensional Euclidean space with a family of attraction/repulsion function is proposed in this article. The stability of aggregating behavior of the swarms system are verified by practical stability theoretical analysis and numerical simulation. Practical stability analysis and numerical simulations results further indicate that the individual members ...


Energy Efficient Swing-Back Control for Brachiation Robot

[{u'author_order': 1, u'affiliation': u'Dept. of Micro-Nano Systems Engineering, Nagoya University, Japan. fukuda@mein.nagoya-u.ac.jp', u'full_name': u'Toshio Fukuda'}, {u'author_order': 2, u'affiliation': u'Dept. of Micro-Nano Systems Engineering, Nagoya University, Japan. kojima@mein.nagoya-u.ac.jp', u'full_name': u'Shigetaka Kojima'}, {u'author_order': 3, u'affiliation': u'Dept. of Micro-Nano Systems Engineering, Nagoya University, Japan. sekiyama@mein.nagoya-u.ac.jp', u'full_name': u'Kousuke Sekiyama'}, {u'author_order': 4, u'affiliation': u'Dept. of Intelligent Interaction Technologies, University of Tsukuba, Japan. hase@esys.tsukuba.ac.jp', u'full_name': u'Yasuhisa Hasegawa'}] 2006 IEEE International Symposium on MicroNanoMechanical and Human Science, 2006

In this paper, we propose an energy efficient swing back control for the braciation robot. In the previous work, brachiation controller was composed of two actions: swing-back and locomotion. The purpose of swing-back is to excite robot so as to achieve locomotion successfully. While locomotion action is to move forward by releasing a brun with arm in moving direction and ...


Lessons from ethology for computational models of development

[{u'author_order': 1, u'affiliation': u'Media Lab., MIT, Cambridge, MA, USA', u'full_name': u'B. Blumberg'}, {u'author_order': 2, u'affiliation': u'Media Lab., MIT, Cambridge, MA, USA', u'full_name': u'M. Berlin'}, {u'author_order': 3, u'affiliation': u'Media Lab., MIT, Cambridge, MA, USA', u'full_name': u'D. Buchsbaum'}, {u'author_order': 4, u'affiliation': u'Media Lab., MIT, Cambridge, MA, USA', u'full_name': u'M. Downie'}, {u'author_order': 5, u'affiliation': u'Media Lab., MIT, Cambridge, MA, USA', u'full_name': u'D. Lyons'}, {u'author_order': 6, u'affiliation': u'Media Lab., MIT, Cambridge, MA, USA', u'full_name': u'J. Cochran'}] Proceedings of the International Joint Conference on Neural Networks, 2003., 2003

Summary form only given. Recent results from the ethological literature challenge some widely held views about the development of animal behavior and offer new directions for research into the organization of synthetic behavior systems. The process of development is often seen as one of continual refinement, with infantile behaviors representing the primitive precursors of adult behavior. While this notion is ...


The development of a low cost animal behavior measurement system

[{u'author_order': 1, u'affiliation': u'Dept. of Biomed. Eng., I-Shou Univ., Kaohsiung, Taiwan', u'full_name': u'Y.C. Li'}, {u'author_order': 2, u'full_name': u'M.S. Young'}, {u'author_order': 3, u'full_name': u'S. McPhee'}, {u'author_order': 4, u'full_name': u'G. Johan'}, {u'author_order': 5, u'full_name': u'S.L. Jen'}] Proceedings of the First Joint BMES/EMBS Conference. 1999 IEEE Engineering in Medicine and Biology 21st Annual Conference and the 1999 Annual Fall Meeting of the Biomedical Engineering Society (Cat. N, 1999

In this paper, we introduce a low-cost system for animal behavior measurement. This system includes four animal experiment cages, each cage being attached to a very sensitive vibration sensor. The output signal of each vibration sensor is connected to a four-channel data acquisition system. The vibration sensor we adopt here is modified from a low cost piezoelectric buzzer. The self-made ...


Implantable neuromuscular stimulators used in animal behavior experiments

[{u'author_order': 1, u'affiliation': u'Inst. of Biomed. Eng., CAMS & PUMC, Tianjin, China', u'full_name': u'Sha Hong'}, {u'author_order': 2, u'affiliation': u'Inst. of Biomed. Eng., CAMS & PUMC, Tianjin, China', u'full_name': u'Wang Yan'}, {u'author_order': 3, u'affiliation': u'Inst. of Biomed. Eng., CAMS & PUMC, Tianjin, China', u'full_name': u'Ren Chaoshi'}] Proceedings. 2005 First International Conference on Neural Interface and Control, 2005., 2005

The design of implantable neuromuscular stimulator used in the behavior experiments desires that the stimulator has maximum functionality to meet the need of the implanted device, such as small size, reliable, safe and easy to use. In this thesis, we consider the basic problem above and two types devices of the stimulator are developed. The first device developed uses standard ...


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Educational Resources on Animal behavior

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eLearning

No eLearning Articles are currently tagged "Animal behavior"

IEEE-USA E-Books

  • The Experimental Study and Computer Simulation of Fish Behavior in the Uniform Environment

    We have studied experimentally the carp exploratory behavior in the circular corridor under uniform illumination and in the absence of external landmarks. The behavior was not uniform despite the uniformity of environment The alternation of two modes of behavior, search (accompanied by high turn frequency) and ranging (with few or no turns), was observed. The existence of distinct modes manifested itself in the positive correlation between turn frequencies at successive time intervals, as well as in abrupt switching between high and low turn frequencies. We developed a model based on the one- dimension map: Xn= λnXn−1(1Xn−1), where X is the tendency to turn, and parameter λ is influenced by Gaussian white noise caused by spontaneous nervous activity. There was a correlation between successive values of the tendency, as well as switches from series of low values to series of high ones under influence of the noise. The behavior of the model is the case of noise- induced phase transitions and matches experimental data qualitatively. It is concluded that a noise generated by the nervous system can play a role in the shaping of animal behavior.

  • A Bottom-Up Mechanism for Behavior Selection in an Artificial Creature

    In this paper we propose a mechanism for motivational competition and selection of behavior. One important characteristic of this mechanism is that the selection of behavior is modelled as an emergent property of a parallel process. This in contrast with mechanisms for behavior selection and motivational competition proposed earlier, which are based on a hierarchical. preprogrammed control structure. We show that selection of behavior can be modeled in a bottom-up way using an activation/inhibition dynamics among the different behaviors that can be selected. There is no weighing up of behaviors in a cognitive manner and neither are hierarchical or bureaucratic structures imposed. The paper elaborates upon the results we obtained with simulated creatures based on this mechanism. It draws parallels between characteristics observed in animal behavior and characteristics demonstrated by our artificial creatures. Examples are: displacement behavior, opportunistic behavior, fatigue, selective attention, and so on.

  • Modeling Adaptive Autonomous Agents

    One category of research in Artificial Life is concerned with modeling and building so-called adaptive autonomous agents, which are systems that inhabit a dynamic, unpredictable environment in which they try to satisfy a set of time-dependent goals or motivations. Agents are said to be adaptive if they improve their competence at dealing with these goals. based on experience. Autonomous agents constitute a new approach to the study of Artificial Intelligence (AI), which is highly inspired by biology, in particular ethology, the study of animal behavior. Research in autonomous agents has brought about a new wave of excitement into the field of AI. This paper reflects on the state of the art of this new approach. It attempts to extract its main ideas, evaluates what contributions have been made so far, and identifies its current limitations and open problems.

  • Evolving Imitating Agents and the Emergence of a Neural Mirror System

    Imitation is a highly complex cognitive process, employing vision, perception, representation, memory and motor control. The underlying mechanisms that give rise to imitative behavior have attracted a lot of attention in recent years and have been the subject of research in various disciplines, from neuroscience to animal behavior and human psychology. In particular, studies in monkeys and humans have discovered a neural mirror system that demonstrates an internal correlation between the representations of perceptual and motor functionalities. In contradistinction to previous engineering-based approaches, we focus on the evolutionary origins of imitation and present a novel framework for studying the emergence of imitative behavior. We successfully develop evolutionary adaptive autonomous agents that spontaneously demonstrate imitative learning, facilitating a comprehensive study of the emerging underlying neural mechanisms. Interestingly, some of these agents are found to embody a neural “mirror” device analogous to those identified in biological systems. Further analysis of these agents' networks reveals complex dynamics, combining innate perceptual-motor coupling with acquired context-action associations, to accomplish the required task.

  • Towards a comprehensive Alife-model of the evolution of the nervous system and adaptive behavior

    The potentials and tools that are offered by Alife for biology in modeling the nervous system and animal behavior are mainly unexploited. There is no consistent Alife model of the biological evolution of the nervous system as yet. whereas the modeling tools are at hand and their application for this purpose seems evident. In a biologically grounded model we have to make every possible effort to use principles known from biology, and to minimize the arbitrarily employed organizing rules. The aim of our work is to create a biologically accurate Alife model of the formation and evolution of the nervous system in connection with the adaptive behavior. In this article we concentrate on the structure of the modeled genome, which is the basis of playing a double biological role: to ensure an open-ended evolutionary process, as well as to direct the ontogenesis. The main questions we examined are: what are the basic rules of construction that are sufficient to create a workable nervous system and how can we model them in a biologically realistic way?

  • How insects learn about the sun's course: alternative modeling approaches

    One of the major puzzles in animal behavior, arid a major problem to be solved in the design of robots, concerns how spatial patterns in the environment can be encoded internally and used for navigation in a complex natural environment. Most work on this issue has concerned landmark learning. This paper deals with a phenomenon of spatial learning that is at least as widespread in the animal world as landmark learning, but has received comparatively little attention. The phenomenon is the ability to learn the course of the sun relative to earth-bound features, and thus to use the sun as a true compass. After reviewing behavioral evidence from bees and ants, two particularly well studied species, we evaluate the applicability of symbolic and connectionist approaches to modeling the internal representation of this environmental pattern.

  • Toward Synthesizing Artificial Neural Networks that Exhibit Cooperative Intelligent Behavior: Some Open Issues in Artificial Life

    The tasks that animals perform require a high degree of intelligence. Animals forage for food, migrate, navigate, court mates, rear offspring, defend against predators, construct nests, and so on. These tasks commonly require social interaction/cooperation and are accomplished by animal nervous systems, which are the result of billions of years of evolution and complex developmental/learning processes. The Artificial Life (AL) approach to synthesizing intelligent behavior is guided by this biological perspective. In this article we examine some of the numerous open problems in synthesizing intelligent animal behavior (especially cooperative behavior involving communication) that face the field of AL, a discipline still in its infancy.



Standards related to Animal behavior

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