Software Agents

being used, and touted, for applications as diverse as personalised information management, electronic commerce, interface design, computer games, and management of complex commercial and industrial processes. Despite this proliferation, there is, as yet, no commonly agreed upon definition of exactly what an agent is — Smith et al. (1994) define it as “a persistent software entity dedicated to a specific purpose”; Selker (1994) takes agents to be “computer programs that simulate a human relationship by doing something that another person could do for you”; and Janca (1995) defines an agent as “a software entity to which tasks can be delegated”. To capture this variety, a relatively loose notion of an agent as a self-contained program capable of controlling its own decision making and acting, based on its perception of its environment, in pursuit of one or more objectives will be used here. Within the extant applications, three distinct classes of agent can be identified. At the simplest level, there are “gopher ” agents, which execute straightforward tasks based on pre-specified rules and assumptions (eg inform me when the share price deviates by 10 % from its mean position or tell me when I need to reorder stock items). The next level of sophistication involves “service performing” agents, which execute a well defined task at the request of a user (eg find me the cheapest flight to Paris or arrange a meeting with the managing director some day next week). Finally, there are “predictive ” agents, which volunteer information or services to a user, without being explicitly asked, whenever it is deemed appropriate (eg an agent may monitor newsgroups on the INTERNET and return discussions that it believes to be of interest to the user or a holiday agent may inform its user that a travel firm is offering large discounts on holidays to South Africa knowing that the user is interested in safaris). Common to all these classes are the following key hallmarks of agenthoo

Pitfalls of Agent-Oriented Development

While the theoretical and experimental foundations of agent-based systems are becoming increasingly well understood, comparatively little effort has been devoted to understanding the pragmatics of (multi-) agent systems development - the everyday reality of carrying out an agent-based development project. As a result, agent system developers are needlessly repeating the same mistakes, with the result that, at best, resources are wasted - at worst, projects fail. This paper identifies the main pitfalls that await the agent system developer, and where possible, makes tentative recommendations for how these pitfalls can be avoided or rectified

Improving the Scalability of Multi-Agent Systems

There is an increasing demand for designers and developers to construct ever larger multi-agent systems. Such systems will be composed of hundreds or even thousands of autonomous agents. Moreover, in open and dynamic environments, the number of agents in the system at any one time will fluctuate significantly. To cope with these twin issues of scalability and variable numbers, we hypothesize that multi-agent systems need to be both /self-building/ (able to determine the most appropriate organizational structure for the system by themselves at run-time) and /adaptive/ (able to change this structure as their environment changes). To evaluate this hypothesis we have implemented such a multi-agent system and have applied it to the domain of automated trading. Preliminary results supporting the first part of this hypothesis are presented: adaption and self-organization do indeed make the system better able to cope with large numbers of agents

On the Identification of Agents in the Design of Production Control Systems

This paper describes a methodology that is being developed for designing and building agent-based systems for the domain of production control. In particular, this paper deals with the steps that are involved in identifying the agents and in specifying their responsibilities. The methodology aims to be usable by engineers who have a background in production control but who have no prior experience in agent technology. For this reason, the methodology needs to be very prescriptive with respect to the agent-related aspects of design

Microstructure versus Size: Mechanical Properties of Electroplated Single Crystalline Cu Nanopillars

We report results of uniaxial compression experiments on single-crystalline Cu nanopillars with nonzero initial dislocation densities produced without focused ion beam (FIB). Remarkably, we find the same power-law size-driven strengthening as FIB-fabricated face-centered cubic micropillars. TEM analysis reveals that initial dislocation density in our FIB-less pillars and those produced by FIB are on the order of 10^(14)  m^(-2) suggesting that mechanical response of nanoscale crystals is a stronger function of initial microstructure than of size regardless of fabrication method

MAGSAT data processing: A report for investigators

The in-flight attitude and vector magnetometer data bias recovery techniques and results are described. The attitude bias recoveries are based on comparisons with a magnetic field model and are thought to be accurate to 20 arcsec. The vector magnetometer bias recoveries are based on comparisons with the scalar magnetometer data and are thought to be accurate to 3 nT or better. The MAGSAT position accuracy goals of 60 m radially and 300 m horizontally were achieved for all but the last 3 weeks of Magsat lifetime. This claim is supported by ephemeris overlap statistics and by comparisons with ephemerides computed with an independent orbit program using data from an independent tracking network. MAGSAT time determination accuracy is estimated at 1 ms. Several errors in prelaunch assumptions regarding data time tags, which escaped detection in prelaunch data tests, and were discovered and corrected postlaunch are described. Data formats and products, especially the Investigator-B tapes, which contain auxiliary parameters in addition to the basic magnetometer and ephemeris data, are described

Breaking the habit: measuring and predicting departures from routine in individual human mobility

Researchers studying daily life mobility patterns have recently shown that humans are typically highly predictable in their movements. However, no existing work has examined the boundaries of this predictability, where human behaviour transitions temporarily from routine patterns to highly unpredictable states. To address this shortcoming, we tackle two interrelated challenges. First, we develop a novel information-theoretic metric, called instantaneous entropy, to analyse an individual’s mobility patterns and identify temporary departures from routine. Second, to predict such departures in the future, we propose the first Bayesian framework that explicitly models breaks from routine, showing that it outperforms current state-of-the-art predictor

Irradiated asymmetric Friedmann branes

We consider a Friedmann brane moving in a bulk impregnated by radiation. The setup is strongly asymmetric, with only one black hole in the bulk. The radiation emitted by this bulk black hole can be reflected, absorbed or transmitted through the brane. Radiation pressure accelerates the brane, behaving as dark energy. Absorption however generates a competing effect: the brane becomes heavier and gravitational attraction increases. We analyse the model numerically, assuming a total absorbtion on the brane for k=1. We conclude that due to the two competing effects, in this asymmetric scenario the Hawking radiation from the bulk black hole is not able to change the recollapsing fate of this brane-world universe. We show that for light branes and early times the radiation pressure is the dominant effect. In contrast, for heavy branes the self-gravity of the absorbed radiation is a much stronger effect. We find the critical value of the initial energy density for which these two effects roughly cancel each other.Comment: 27 pages, 12 figure

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