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.

Artificial keys for botanical identification using a multilayer perceptron neural network (MLP)

In this paper, practical generation of identification keys for biological taxa using a multilayer perceptron neural network is described. Unlike conventional expert systems, this method does not require an expert for key generation, but is merely based on recordings of observed character states. Like a human taxonomist, its judgement is based on experience, and it is therefore capable of generalized identification of taxa. An initial study involving identification of three species of Iris with greater than 90% confidence is presented here. In addition, the horticulturally significant genus Lithops (Aizoaceae/Mesembryanthemaceae), popular with enthusiasts of succulent plants, is used as a more practical example, because of the difficulty of generation of a conventional key to species, and the existence of a relatively recent monograph. It is demonstrated that such an Artificial Neural Network Key (ANNKEY) can identify more than half (52.9%) of the species in this genus, after training with representative data, even though data for one character is completely missing.

Detection of Parkinson’s disease tremor-onset with a frequency analysing artificial neural network

Deep Brain Stimulator devices are becoming widely used for therapeutic benefits in movement disorders such as Parkinson's disease. Prolonging the battery life span of such devices could dramatically reduce the risks and accumulative costs associated with surgical replacement. This paper demonstrates how an artificial neural network can be trained using pre-processing frequency analysis of deep brain electrode recordings to detect the onset of tremor in Parkinsonian patients. Implementing this solution into an 'intelligent' neurostimulator device will remove the need for continuous stimulation currently used, and open up the possibility of demand-driven stimulation. Such a methodology could potentially decrease the power consumption of a deep brain pulse generator.

A geometric algorithm for an artificial life form based on anachronistic methods

Modern methods of spawning new technological motifs are not appropriate when it is desired to realize artificial life as an actual real world entity unto itself (Pattee 1995; Brooks 2006; Chalmers 1995). Many fundamental aspects of such a machine are absent in common methods, which generally lack methodologies of construction. In this paper we mix classical and modern studies in order to attempt to realize an artificial life form from first principles. A model of an algorithm is introduced, its methodology of construction is presented, and the fundamental source from which it sprang is discussed.

Ex Vivo Construction of an Artificial Ocular Surface by Combination of Corneal Limbal Epithelial Cells and a Compressed Collagen Scaffold Containing Keratocytes

We have investigated the use of a laminin coated compressed collagen gel containing corneal fibroblasts (keratocytes) as a novel scaffold to support the growth of corneal limbal epithelial stem cells. The growth of limbal epithelial cells was compared between compressed collagen gel and a clinically proven conventional substrate, denuded amniotic membrane. Following compression of the collagen gel, encapsulated keratocytes remained viable and scanning electron microscopy showed that fibres within the compressed gel were dense, homogeneous and similar in structure to those within denuded amniotic membrane. Limbal epithelial cells were successfully expanded upon the compressed collagen resulting in stratified layers of cells containing desmosome and hemidesmosome structures. The resulting corneal constructs of both the groups shared a high degree of transparency, cell morphology and cell stratification. Similar protein expression profiles for cytokeratin 3 and cytokeratin 14 and no significant difference in cytokeratin 12 mRNA expression levels by real time PCR were also observed. This study provides the first line of evidence that a laminin coated compressed collagen gel containing keratocytes can adequately support limbal epithelial cell expansion, stratification and differentiation to a degree that is comparable to the leading conventional scaffold, denuded amniotic membrane.

The influence of different artificial soil types on the acute toxicity of carbendazim to the earthworm Eisenia fetida in laboratory toxicity tests

Field populations of earthworms have shown a varied response in mortality to the fungicide carbendazim, the toxic reference substance used in agrochemical field trials. The aim of this study was to determine the influence of soil conditions as a potential cause of this variation. Laboratory acute toxicity tests were conducted using a range of artificial soils with varying soil components (organic matter, clay, pH and moisture). Batch adsorption/desorption studies were run to determine the influence of the soil properties on carbendazim behaviour. Adsorption was shown to be correlated with organic matter content and pH and this in turn could be linked to Eisenia fetida mortality, with lower mortality occurring with increased adsorption. Overall while E.fetida mortality did vary significantly between several of the soils the calculated LC50 values in the different soils did not cover a wide range (6.04-16.00 mg kg(-1)), showing that under these laboratory conditions soil components did not greatly influence carbendazim toxicity to E.fietida. (c) 2007 Elsevier Masson SAS. All rights reserved.

Use of an artificial root to examine the influence of 8-hydroxyquinoline on soil microbial activity and bacterial community structure

Invasive plant species have been shown to alter the microbial community composition of the soils they invade and it is suggested that this below-ground perturbation of potential pathogens, decomposers or symbionts may feedback positively to allow invasive success. Whether these perturbations are mediated through specific components of root exudation are not understood. We focussed on 8-hydroxyquinoline, a putative allelochemical of Centaurea diffusa (diffuse knapweed) and used an artificial root system to differentiate the effects of 8-hydroxyquinoline against a background of total rhizodeposition as mimicked through supply of a synthetic exudate solution. In soil proximal (0-10 cm) to the artificial root, synthetic exudates had a highly significant (P < 0.001) influence on dehydrogenase, fluorescein diacetate hydrolysis and urease activity. in addition, 8-hydroxyquinoline was significant (p = 0.003) as a main effect on dehydrogenase activity and interacted with synthetic exudates to affect urease activity (p = 0.09). Hierarchical cluster analysis of 16S rDNA-based DGGE band patterns also identified a primary affect of synthetic exudates and a secondary affect of 8-hydroxyquinoline on bacterial community structure. Thus, we show that the artificial rhizosphere produced by the synthetic exudates was the predominant effect, but, that the influence of the 8-hydroxyquinoline signal on the activity and structure of soil microbial communities could also be detected. (C) 2009 Elsevier Ltd. All rights reserved.

Implicit and explicit knowledge bases in artificial grammar learning

Two experiments examined the claim for distinct implicit and explicit learning modes in the artificial grammar-learning task (Reber, 1967, 1989). Subjects initially attempted to memorize strings of letters generated by a finite-state grammar and then classified new grammatical and nongrammatical strings. Experiment 1 showed that subjects' assessment of isolated parts of strings was sufficient to account for their classification performance but that the rules elicited in free report were not sufficient. Experiment 2 showed that performing a concurrent random number generation task under different priorities interfered with free report and classification performance equally. Furthermore, giving different groups of subjects incidental or intentional learning instructions did not affect classification or free report.

Artificial ants for active routing

Ant colonies in nature provide a good model for a distributed, robust and adaptive routing algorithm. This paper proposes the adoption of the same strategy for the routing of packets in an Active Network. Traditional store-and-forward routers are replaced by active intermediate systems, which are able to perform computations on transient packets, in a way that results very helpful for developing and dynamically deploying new protocols. The adoption of the Active Networks paradigm associated with a cooperative learning environment produces a robust, decentralized routing algorithm capable of adapting to network traffic conditions.