17,126 research outputs found
Applications of Biological Cell Models in Robotics
In this paper I present some of the most representative biological models
applied to robotics. In particular, this work represents a survey of some
models inspired, or making use of concepts, by gene regulatory networks (GRNs):
these networks describe the complex interactions that affect gene expression
and, consequently, cell behaviour
Memory and information processing in neuromorphic systems
A striking difference between brain-inspired neuromorphic processors and
current von Neumann processors architectures is the way in which memory and
processing is organized. As Information and Communication Technologies continue
to address the need for increased computational power through the increase of
cores within a digital processor, neuromorphic engineers and scientists can
complement this need by building processor architectures where memory is
distributed with the processing. In this paper we present a survey of
brain-inspired processor architectures that support models of cortical networks
and deep neural networks. These architectures range from serial clocked
implementations of multi-neuron systems to massively parallel asynchronous ones
and from purely digital systems to mixed analog/digital systems which implement
more biological-like models of neurons and synapses together with a suite of
adaptation and learning mechanisms analogous to the ones found in biological
nervous systems. We describe the advantages of the different approaches being
pursued and present the challenges that need to be addressed for building
artificial neural processing systems that can display the richness of behaviors
seen in biological systems.Comment: Submitted to Proceedings of IEEE, review of recently proposed
neuromorphic computing platforms and system
The fallacy of general purpose bio-inspired computing
Bio-inspired computing comes in many flavours, inspired by biological systems from which salient features and/or organisational principles have been idealised and abstracted. These bio-inspired schemes have sometimes been demonstrated to be general purpose; able to approximate arbitrary dynamics, encode arbitrary structures, or even carry out universal computation. The generality of these abilities is typically (although often implicitly) reasoned to be an attractive and worthwhile trait. Here, it is argued that such reasoning is fallacious. Natural systems are nichiversal rather than universal, and we should expect the computational systems that they inspire to be similarly limited in their performance, even if they are ultimately capable of generality in their competence. Practical and methodological implications of this position for the use of bio-inspired computing within artificial life are outlined
- …