Artificial Intelligence: the basics

Artificial Intelligence: The Basics is a concise and cutting-edge introduction to the fast moving world of AI. The author Kevin Warwick, a pioneer in the field, examines issues of what it means to be man or machine and looks at advances in robotics which have blurred the boundaries. Topics covered include: how intelligence can be defined, whether machines can 'think', sensory input in machine systems, the nature of consciousness, the controversial culturing of human neurons. Exploring issues at the heart of the subject, this book is suitable for anyone interested in AI, and provides an illuminating and accessible introduction to this fascinating subject.

A model of UK domestic appliance-use using Artificial Neural Networks

The development of an Artificial Neural Network model of UK domestic appliance energy consumption is presented. The model uses diary-style appliance use data and a survey questionnaire collected from 51 households during the summer of 2010. It also incorporates measured energy data and is sensitive to socioeconomic, physical dwelling and temperature variables. A prototype model is constructed in MATLAB using a two layer feed forward network with backpropagation training and has a12:10:24architecture.Model outputs include appliance load profiles which can be applied to the fields of energy planning (micro renewables and smart grids), building simulation tools and energy policy.

Drivers of increased soil respiration in a poplar coppice exposed to elevated CO2

Background and Aims. The response of soil respiration (SR) to elevated CO2 is driven by a number of processes and feedbacks. This work aims to i) detect the effect of elevated CO2 on soil respiration during the second rotation of a short rotation forest, at two levels of N availability; and ii) identify the main drivers behind any changes in soil respiration. Methods. A poplar plantation (POP-EUROFACE) was grown for two rotations of three years under elevated CO2 maintained by a FACE (Free Air CO2 Enrichment) technique. Root biomass, litter production and soil respiration were followed for two consecutive years after coppice. Results. In the plantation, the stimulation of fine root and litter production under elevated CO2 observed at the beginning of the rotation declined over time. Soil respiration (SR) was continuously stimulated by elevated CO2, with a much larger enhancement during the growing (up to 111 %) than in the dormant season (40 %). The SR increase at first appeared to be due to the increase in fine root biomass, but at the end of the 2nd rotation was supported by litter decomposition and the availability of labile C. Soil respiration increase under elevated CO2 was not affected by N availability. Conclusions. The stimulation of SR by elevated CO2 was sustained by the decomposition of above and belowground litter and by the greater availability of easily decomposable substrates into the soil. C losses through SR were greater in the last year of the plantation due to a lack of effect of elevated CO2 on C allocation to roots, reducing the potential for C accumulation.

The link between temporal attention and emotion: a playground for psychology, neuroscience, and plausible artificial neural networks

In this paper, we will address the endeavors of three disciplines, Psychology, Neuroscience, and Artificial Neural Network (ANN) modeling, in explaining how the mind perceives and attends information. More precisely, we will shed some light on the efforts to understand the allocation of attentional resources to the processing of emotional stimuli. This review aims at informing the three disciplines about converging points of their research and to provide a starting point for discussion.

Pricing and hedging short sterling options using artificial neural networks

This paper compares the performance of artificial neural networks (ANNs) with that of the modified Black model in both pricing and hedging Short Sterling options. Using high frequency data, standard and hybrid ANNs are trained to generate option prices. The hybrid ANN is significantly superior to both the modified Black model and the standard ANN in pricing call and put options. Hedge ratios for hedging Short Sterling options positions using Short Sterling futures are produced using the standard and hybrid ANN pricing models, the modified Black model, and also standard and hybrid ANNs trained directly on the hedge ratios. The performance of hedge ratios from ANNs directly trained on actual hedge ratios is significantly superior to those based on a pricing model, and to the modified Black model.