© Springer International Publishing AG 2018. In this position paper we propose the approach to use “Thinking-Understanding” architecture for the management of the real-time operated robotic system. Based on the “Robot dream” architecture, the robotic system digital input is been translated in form of “pseudo-spikes” and provided to a simulated spiking neural network, then elaborated and fed back to a robotic system as updated behavioural strategy rules. We present the reasoning rule-based system for intelligent spike processing translating spikes into software actions or hardware signals is thus specified. The reasoning is based on pattern matching mechanisms that activates critics that in their turn activates other critics or ways to think...
Spiking neural networks in-silico can closely resemble the architecture and dynamics of neural netwo...
An artificial intelligent agent needs to be equipped with a multitude of abilities in order to inter...
We present here a learning system using the iCub humanoid robot and the SpiNNaker neuromorphic chip ...
© Springer International Publishing AG 2018. In this position paper we propose the approach to use “...
© 2017 IEEE. In this position paper the newel approach for the spiking reasoning system for the real...
© Springer International Publishing Switzerland 2016.In this position paper we present a novel appro...
This study explores the design and control of the behaviour of agents and robots using simple circui...
© 2016, Springer Science+Business Media New York.In this paper, we present the next step in our appr...
Neuromorphic engineers develop event-based spiking neural networks (SNNs) in hardware. These SNNs cl...
AbstractWe describe a sequence of experiments in which a robot “brain” was evolved to mimic the beha...
Abstract—In this paper, we introduce a network of spiking neurons devoted to navigation control. Thr...
To understand how animals and humans learn, form memories and make decisions is along-lasting goal i...
Artificial neural networks have a wide range of applications nowadays in which they are used for int...
Robots are entering our daily lives from self-driving cars to health-care robots. Historically, pre-...
© 2015, Springer Science+Business Media New York. Learning classifier systems (LCS) are population-b...
Spiking neural networks in-silico can closely resemble the architecture and dynamics of neural netwo...
An artificial intelligent agent needs to be equipped with a multitude of abilities in order to inter...
We present here a learning system using the iCub humanoid robot and the SpiNNaker neuromorphic chip ...
© Springer International Publishing AG 2018. In this position paper we propose the approach to use “...
© 2017 IEEE. In this position paper the newel approach for the spiking reasoning system for the real...
© Springer International Publishing Switzerland 2016.In this position paper we present a novel appro...
This study explores the design and control of the behaviour of agents and robots using simple circui...
© 2016, Springer Science+Business Media New York.In this paper, we present the next step in our appr...
Neuromorphic engineers develop event-based spiking neural networks (SNNs) in hardware. These SNNs cl...
AbstractWe describe a sequence of experiments in which a robot “brain” was evolved to mimic the beha...
Abstract—In this paper, we introduce a network of spiking neurons devoted to navigation control. Thr...
To understand how animals and humans learn, form memories and make decisions is along-lasting goal i...
Artificial neural networks have a wide range of applications nowadays in which they are used for int...
Robots are entering our daily lives from self-driving cars to health-care robots. Historically, pre-...
© 2015, Springer Science+Business Media New York. Learning classifier systems (LCS) are population-b...
Spiking neural networks in-silico can closely resemble the architecture and dynamics of neural netwo...
An artificial intelligent agent needs to be equipped with a multitude of abilities in order to inter...
We present here a learning system using the iCub humanoid robot and the SpiNNaker neuromorphic chip ...