Neurorobotics—A Thriving Community and a Promising Pathway Toward Intelligent Cognitive Robots

Krichmar, Jeffrey L.

doi:10.3389/fnbot.2018.00042

Cited by 48 publications

(29 citation statements)

References 76 publications

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“…But merging OS and DS in SNN paradigm is still unexplored. Furthermore, given that the relationship between orientation and direction selectivity remains to be investigated at the behavioral level, this research aims to embody these two related processes in virtual and physical robots as a proof of concept (Pezzulo et al, 2011 ; Krichmar, 2018 ). In this perspective, the present model was evaluated under an operant conditioning context, modulating its behavioral response when shown basic orientated stimuli in motion.…”

Section: Introductionmentioning

confidence: 99%

Spiking Neurons Integrating Visual Stimuli Orientation and Direction Selectivity in a Robotic Context

et al. 2018

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Visual motion detection is essential for the survival of many species. The phenomenon includes several spatial properties, not fully understood at the level of a neural circuit. This paper proposes a computational model of a visual motion detector that integrates direction and orientation selectivity features. A recent experiment in the Drosophila model highlights that stimulus orientation influences the neural response of direction cells. However, this interaction and the significance at the behavioral level are currently unknown. As such, another objective of this article is to study the effect of merging these two visual processes when contextualized in a neuro-robotic model and an operant conditioning procedure. In this work, the learning task was solved using an artificial spiking neural network, acting as the brain controller for virtual and physical robots, showing a behavior modulation from the integration of both visual processes.

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Section: Introductionmentioning

confidence: 99%

Spiking Neurons Integrating Visual Stimuli Orientation and Direction Selectivity in a Robotic Context

et al. 2018

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“…Despite significant work in transfer learning and domain adaptation, modern systems are largely restricted in their domain of application. The lack of behavior-based concept representation may be a limiting factor in current state-of-the-art systems (Hay et al 2018;Krichmar 2018;Falotico et al 2017). Simulations of simple, embodied organisms with realistic virtual environments may provide platforms for AI research aimed at understanding the interplay between concept representation and embodiment.…”

Section: Integrative Biological Simulationmentioning

confidence: 99%

Integrative biological simulation, neuropsychology, and AI safety

Sarma

Safron

Hay³

2019

Preprint

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We describe a biologically-inspired research agenda with parallel tracks aimed at AI and AI safety. The bottom-up component consists of building a sequence of biophysically realistic simulations of simple organisms such as the nematode Caenorhabditis elegans, the fruit fly Drosophila melanogaster, and the zebrafish Danio rerio to serve as platforms for research into AI algorithms and system architectures. The top-down component consists of an approach to value alignment that grounds AI goal structures in neuropsychology, broadly considered. Our belief is that parallel pursuit of these tracks will inform the development of value-aligned AI systems that have been inspired by embodied organisms with sensorimotor integration. An important set of side benefits is that the research trajectories we describe here are grounded in long-standing intellectual traditions within existing research communities and funding structures. In addition, these research programs overlap with significant contemporary themes in the biological and psychological sciences such as data/model integration and reproducibility.

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“…Despite significant work in transfer learning and domain adaptation, modern systems are largely restricted in their domain of application. The lack of behavior-based concept representation may be a limiting factor in current state-of-the-art systems Krichmar 2018;Falotico et al 2017). Simulations of simple, embodied organisms with realistic virtual environments may provide platforms for AI research aimed at understanding the interplay between concept representation and embodiment.…”

Section: Integrative Biological Simulationmentioning

confidence: 99%

Integrative biological simulation, neuropsychology, and AI safety

Sarma

Safron

Hay³

2018

Preprint

View full text Add to dashboard Cite

We propose a biologically-inspired research agenda with parallel tracks aimed at AI and AI safety. The bottom-up component consists of building a sequence of biophysically realistic simulations of simple organisms such as the nematode Caenorhabditis elegans, the fruit fly Drosophila melanogaster, and the zebrafish Danio rerio to serve as platforms for research into AI algorithms and system architectures. The top-down component consists of an approach to value alignment that grounds AI goal structures in neuropsychology. Our belief is that parallel pursuit of these tracks will inform the development of value-aligned AI systems that have been inspired by embodied organisms with sensorimotor integration. An important set of side benefits is that the research trajectories we describe here are grounded in long-standing intellectual traditions within existing research communities and funding structures. In addition, these research programs overlap with significant contemporary themes in the biological and psychological sciences such as data/model integration and reproducibility.

show abstract

Neurorobotics—A Thriving Community and a Promising Pathway Toward Intelligent Cognitive Robots

Cited by 48 publications

References 76 publications

Spiking Neurons Integrating Visual Stimuli Orientation and Direction Selectivity in a Robotic Context

Spiking Neurons Integrating Visual Stimuli Orientation and Direction Selectivity in a Robotic Context

Integrative biological simulation, neuropsychology, and AI safety

Integrative biological simulation, neuropsychology, and AI safety

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