Dynamics of a reverberating neural net is studied by means of computer simulation. The net, which is composed of 9 leaky integrate-and-fire (LIF) neurons arranged in a square lattice, is fully connected with interneuronal communication delay proporti...
Recent studies on the theoretical performance of latency and rate code in single neurons have revealed that the ultimate accuracy is affected in a nontrivial way by aspects such as the level of spontaneous activity of presynaptic neurons, amount of n...
In this paper, we show how to extend our previously proposed novel continuous time Recurrent Neural Networks (RNN) approach that retains the advantage of continuous dynamics offered by Ordinary Differential Equations (ODE) while enabling parameter es...
Multi-layer perceptron artificial neural networks (MLP-ANNs) were used to predict the concentration of digoxin needed to obtain a cardio-activity of specific biophysical parameters in Tivela stultorum hearts. The inputs of the neural networks were th...
In this paper, we numerically study the effect of spike-timing-dependent plasticity (STDP) on synchronization transitions induced by autaptic activity in adaptive Newman-Watts Hodgkin-Huxley neuron networks. It is found that synchronization transitio...
Embodied cognition is a hot topic in both cognitive science and AI, despite the fact that there still is relatively little consensus regarding what exactly constitutes 'embodiment'. While most embodied AI and cognitive robotics research views the bod...
DNA Fragment assembly - an NP-Hard problem - is one of the major steps in of DNA sequencing. Multiple strategies have been used for this problem, including greedy graph-based algorithms, deBruijn graphs, and the overlap-layout-consensus approach. Thi...
The aim of this paper is to propose that current robotic technologies cannot have intentional states any more than is feasible within the sensorimotor variant of embodied cognition. It argues that anticipation is an emerging concept that can provide ...
Some of the authors have previously proposed a cognitively inspired reinforcement learning architecture (LS-Q) that mimics cognitive biases in humans. LS-Q adaptively learns under uniform, coarse-grained state division and performs well without param...
This paper proposes and evaluates a solution to the truck redistribution problem prominent in London's Santander Cycle scheme. Due to the complexity of this NP-hard combinatorial optimisation problem, no efficient optimisation techniques are known to...