Using fractals and power laws to predict the location of mineral deposits

Around the world the mineral exploration industry is interested in getting that small increase in probability measure on the earth's surface of where the next large undiscovered deposit might be found. In particular WMC Resources Ltd has operations world wide looking for just that edge in the detection of very large deposits of, for example, gold. Since the pioneering work of Mandelbrot, geologists have been familiar with the concept of fractals and self similarity over a few orders of magnitude for geological features. This includes the location and size of deposits within a particular mineral province. Fractal dimensions have been computed for such provinces and similarities of these aggregated measures between provinces have been noted. This paper explores the possibility of making use of known information to attempt the inverse process. That is, from lesser dimensional measures of a mineral province, for example, fractal dimension or more generally multi-fractal measures, is it possible to infer, even with small increase in probability, where the unknown (preferably large) deposits might be located

TRAVOS: Trust and Reputation in the Context of Inaccurate Information Sources

In many dynamic open systems, agents have to interact with one another to achieve their goals. Here, agents may be self-interested, and when trusted to perform an action for another, may betray that trust by not performing the action as required. In addition, due to the size of such systems, agents will often interact with other agents with which they have little or no past experience. There is therefore a need to develop a model of trust and reputation that will ensure good interactions among software agents in large scale open systems. Against this background, we have developed TRAVOS (Trust and Reputation model for Agent-based Virtual OrganisationS) which models an agent's trust in an interaction partner. Specifically, trust is calculated using probability theory taking account of past interactions between agents, and when there is a lack of personal experience between agents, the model draws upon reputation information gathered from third parties. In this latter case, we pay particular attention to handling the possibility that reputation information may be inaccurate

Transient excitation and data processing techniques employing the fast fourier transform for aeroelastic testing

The development of testing techniques useful in airplane ground resonance testing, wind tunnel aeroelastic model testing, and airplane flight flutter testing is presented. Included is the consideration of impulsive excitation, steady-state sinusoidal excitation, and random and pseudorandom excitation. Reasons for the selection of fast sine sweeps for transient excitation are given. The use of the fast fourier transform dynamic analyzer (HP-5451B) is presented, together with a curve fitting data process in the Laplace domain to experimentally evaluate values of generalized mass, model frequencies, dampings, and mode shapes. The effects of poor signal to noise ratios due to turbulence creating data variance are discussed. Data manipulation techniques used to overcome variance problems are also included. The experience is described that was gained by using these techniques since the early stages of the SST program. Data measured during 747 flight flutter tests, and SST, YC-14, and 727 empennage flutter model tests are included

Searching for Color Coherent Effects at Intermediate Q2Q^2 via Double Scattering Processes

We propose that measuring the $Q^2$ dependence of the number of final-state interactions of the recoil protons in quasi-elastic electron scattering from light nuclei is a new method to investigate Color Coherent effects at {\bf intermediate} values of $Q^2$ ({$\sim$ few $(GeV/c)^2$}). This is instead of measuring events without final-state interactions. Our calculations indicate that such measurements could reveal significant color transparency effects for the highest of the energies initially available at CEBAF. Measurements that detect more than one hadron in the final state, which require the use of large acceptance ($4\pi$) detectors, are required.Comment: 19 pages in RevTex, 5 postscript figures available from [email protected]

Low Temperature Physics

Contains research objectives and reports on one research project

The ART of IAM: The Winning Strategy for the 2006 Competition

In many dynamic open systems, agents have to interact with one another to achieve their goals. Here, agents may be self-interested, and when trusted to perform an action for others, may betray that trust by not performing the actions as required. In addition, due to the size of such systems, agents will often interact with other agents with which they have little or no past experience. This situation has led to the development of a number of trust and reputation models, which aim to facilitate an agent's decision making in the face of uncertainty regarding the behaviour of its peers. However, these multifarious models employ a variety of different representations of trust between agents, and measure performance in many different ways. This has made it hard to adequately evaluate the relative properties of different models, raising the need for a common platform on which to compare competing mechanisms. To this end, the ART Testbed Competition has been proposed, in which agents using different trust models compete against each other to provide services in an open marketplace. In this paper, we present the winning strategy for this competition in 2006, provide an analysis of the factors that led to this success, and discuss lessons learnt from the competition about issues of trust in multiagent systems in general. Our strategy, IAM, is Intelligent (using statistical models for opponent modelling), Abstemious (spending its money parsimoniously based on its trust model) and Moral (providing fair and honest feedback to those that request it)

Socially intelligent reasoning for autonomous agents

Socially intelligent agents are autonomous problem solvers that have to achieve their objectives by interacting with other similarly autonomous entities. A major concern, therefore, is with the design of the decision-making mechanism that such agents employ in order to determine which actions to take to achieve their goals. An attractive and much sought after property of this mechanism is that it produces decisions that are rational from the perspective of the individual agent. However, some agents are also inherently social. Moreover, individual and social concerns often conflict, leading to the possibility of inefficient performance of the individual and the system. To address these problems we propose a framework for making socially acceptable decisions, based on social welfare functions, that combines social and individual perspectives in a unified and flexible manner. The framework is realized in an exemplar computational setting and an empirical analysis is made of the relative performance of varying sociable decision-making functions in a range of environments. This analysis is then used to design an agent that adapts its decision-making to reflect the resource constraints that it faces at any given time. A further round of empirical evaluation shows how adding such a metalevel mechanism enhances the performance of the agent by directing reasoning to adopt different strategies in different contexts. Finally, the possibility and efficacy of making the metalevel mechanism adaptive, so that experience of past encounters can be factored into the decision-making, is demonstrated