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Neural Computation in Embodied Closed-Loop Systems for the Generation of Complex Behavior: From Biology to Technology

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Release : 2018-10-11
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Kind : eBook
Book Rating : 056/5 ( reviews)

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Book Synopsis Neural Computation in Embodied Closed-Loop Systems for the Generation of Complex Behavior: From Biology to Technology by : Poramate Manoonpong

Download or read book Neural Computation in Embodied Closed-Loop Systems for the Generation of Complex Behavior: From Biology to Technology written by Poramate Manoonpong. This book was released on 2018-10-11. Available in PDF, EPUB and Kindle. Book excerpt: How can neural and morphological computations be effectively combined and realized in embodied closed-loop systems (e.g., robots) such that they can become more like living creatures in their level of performance? Understanding this will lead to new technologies and a variety of applications. To tackle this research question, here, we bring together experts from different fields (including Biology, Computational Neuroscience, Robotics, and Artificial Intelligence) to share their recent findings and ideas and to update our research community. This eBook collects 17 cutting edge research articles, covering neural and morphological computations as well as the transfer of results to real world applications, like prosthesis and orthosis control and neuromorphic hardware implementation.

Neural Computation in Embodied Closed-Loop Systems for the Generation of Complex Behavior: From Biology to Technology

Download Neural Computation in Embodied Closed-Loop Systems for the Generation of Complex Behavior: From Biology to Technology PDF Online Free

Author :
Release : 2018
Genre :
Kind : eBook
Book Rating : /5 ( reviews)

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Book Synopsis Neural Computation in Embodied Closed-Loop Systems for the Generation of Complex Behavior: From Biology to Technology by :

Download or read book Neural Computation in Embodied Closed-Loop Systems for the Generation of Complex Behavior: From Biology to Technology written by . This book was released on 2018. Available in PDF, EPUB and Kindle. Book excerpt: How can neural and morphological computations be effectively combined and realized in embodied closed-loop systems (e.g., robots) such that they can become more like living creatures in their level of performance? Understanding this will lead to new technologies and a variety of applications. To tackle this research question, here, we bring together experts from different fields (including Biology, Computational Neuroscience, Robotics, and Artificial Intelligence) to share their recent findings and ideas and to update our research community. This eBook collects 17 cutting edge research articles, covering neural and morphological computations as well as the transfer of results to real world applications, like prosthesis and orthosis control and neuromorphic hardware implementation.

Biology-Inspired Engineering and Engineering-Inspired Biology

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Release : 2021-01-04
Genre : Science
Kind : eBook
Book Rating : 40X/5 ( reviews)

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Book Synopsis Biology-Inspired Engineering and Engineering-Inspired Biology by : Jan-Matthias Braun

Download or read book Biology-Inspired Engineering and Engineering-Inspired Biology written by Jan-Matthias Braun. This book was released on 2021-01-04. Available in PDF, EPUB and Kindle. Book excerpt:

Bulletin of the Atomic Scientists

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Release : 1972-10
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Book Synopsis Bulletin of the Atomic Scientists by :

Download or read book Bulletin of the Atomic Scientists written by . This book was released on 1972-10. Available in PDF, EPUB and Kindle. Book excerpt: The Bulletin of the Atomic Scientists is the premier public resource on scientific and technological developments that impact global security. Founded by Manhattan Project Scientists, the Bulletin's iconic "Doomsday Clock" stimulates solutions for a safer world.

Towards an Embodied Understanding of Neural Computation

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Release : 2021
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Book Synopsis Towards an Embodied Understanding of Neural Computation by : Nareg Berberian

Download or read book Towards an Embodied Understanding of Neural Computation written by Nareg Berberian. This book was released on 2021. Available in PDF, EPUB and Kindle. Book excerpt: Information processing systems (IPSs) that behave in the real-world are constantly bombarded with noise from the environment. Although the real-world offers noise for free, this extrinsic noise source has a cost associated to it. The problem is related to the fact that the environmental intricacies (i.e. noisy distribution) in which the IPS samples from is everchanging. Consequently, the IPS is faced with the conundrum of maintaining stability in a dynamic environment, while at the same time, remaining flexible so as to match its intrinsic timescales with the timescales of the environment. Here, we propose conjoining three ingredients for solving the timescale incompatibility issue between IPSs and the environment. First, we propose evolving IPSs in an online fashion such that the system operates on-thefly. Second, we propose the implementation of online operations in robotic hardware - a methodological tool for allowing the IPS to provide feedback during its interaction with the environment. Finally, we propose learning from brain mechanisms as a source of inspiration for building more flexible and adaptive IPSs. In chapter one, we initiate our first attempt towards achieving flexibility in these systems. To this end, we study the interaction between short-term plasticity (STP) and spike-timingdependent plasticity (STDP), two important plasticity rules we've learned from the brain. As such, we construct a microcircuit motif of two units, and show in simulation, how each unit can discriminate the position of a moving stimulus. In chapter two, we study synaptic plasticity in the context of an online robotic domain. To do so, we increase network size to six units, and endow the circuit with STP as a candidate mechanism for microcircuit sensitivity to inputs. Here, we study motion discrimination using a Raspberry Pi microcontroller as the information processing unit. We also use a stationary camera to process images from the real-world. Finally, we attach two LED light sensors for providing feedback of how the system is behaving. Results show that the agent is capable of discriminating the direction of a moving stimulus. In the final chapter of the thesis, we move away from the static online robotic implementation, towards a more dynamic setting. In doing so, we develop a keyboard listener for online mobile robot control. Here, the motor trajectory of the robot is directly linked to network activity of 500 units. Furthermore, the agent is placed in an ecological context where it interacts with a human subject. During human-robot interaction, the motor trajectory of the robot is studied, enabling the human to make inferences about how neural computation is unfolding on-the-fly. The robot illustrates useful properties, one of which is high degree of flexibility and adaptation to ongoing input streams. Overall, we conjoin the three ingredients mentioned above as a framework for solving the timescale incompatibility issue between IPSs and the environment.

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