Agent-oriented techniques represent an exciting new means of analysing, designing and building complex software systems. They have the potential to significantly improve current practice in software engineering and to extend the range of applications that can feasibly be tackled. Yet, to date, there have been few serious attempts to cast agent systems as a software engineering paradigm. This paper seeks to rectify this omission. Specifically, it will be argued that: (i) the conceptual apparatus of agent-oriented systems is well-suited to building software solutions for complex systems and (ii) agent-oriented approaches represent a genuine advance over the current state of the art for engineering complex systems. Following on from this view, the major issues raised by adopting an agent-oriented approach to software engineering are highlighted and discussed.

Classical theories of choice emphasise decision making as a rational process. In general, these theories fail to recognise the formulation stages of a decision and typically can only be applied to problems comprising two or more measurable alternatives. In response to such limitations, numerous descriptive theories have been developed over the last forty years, intended to describe how decisions are made. This paper presents a framework that classifies descriptive theories using a theme of comparison; comparisons involving attributes, alternatives and situations. The paper also reports on research undertaken within a New Zealand local authority. Twenty three senior managers were interviewed about their decision making with the aim of comparing the responses of participants with how the descriptive decision making literature purports decisions are made. Evidence of behaviour consistent with recognised descriptive theories was also investigated. It was found that few managers exhibited behaviour consistent with what is described in the literature. The major difference appears to be the lack of decision formulation contained within most descriptive theories. Descriptive theories are, in general, theories of choice and few decisions described by participants contained a distinct choice phase.

“Somebody says, ‘You know, you people always say that space is continuous. How do you know when you get to a small enough dimension that there really are enough points in between, that it isn’t just a lot of dots separated by little distances? ’ Or they say, ‘You know those quantum mechanical amplitudes you told me about, they’re so complicated and absurd, what makes you think those are right? Maybe they aren’t right. ’ Such remarks are obvious and are perfectly clear to anybody who is working on this problem. It does not do any good to point this out.” —Richard Feynman [1, p.161]

This article presents a framework for emotiolllJl intelligenCl!, a set of skills hypothesized to contribute to the accurate appraisal and expression of emotion in oneself and in others, the effective regulation of emotion in self and others, and the use of feelings to motivate, plan, and achieve in one's life. We start by reviewing the debate about the adaptive versus maladaptive qualities of emotion. We then explore the literature on intelligence, and especiaUy social intelligence. to examine the place of emotion in traditional intelligence conceptions. A framework for integrating the research on emotion-related snUs Is then described. Next, we review the components of emotional intelligence. To conclude the review. the role of emotional intelligence in mental health is discussed and avenues for further investigation are suggested. Is "emotional intelligence " 8 contradiction in terms? One tradition in Western thought has viewed emotions as disorganized interruptions of mental activity, so potentially disruptive that they must be controlled. Writing in the first century B.C., Publilius Syrus stated, "Rule your feelings, lest your feelings rule you " [1}.

“Having looked at monetary policy from both sides now, I can testify that central banking in practice is as much art as science. Nonetheless, while practicing this dark art, I have always found the science quEite useful.” 2 Alan S. Blinder

to solve incremental learning tasks. In this paper, we describe a framework and methodology, called instance-based learning, that generates classification predictions using only specific instances. Instance-based learning algorithms do not maintain a set of abstractions derived from specific instances

[Green and Bavelier, 2003] has grabbed national attention for suggesting that playing “action ” video and computer games has the positive effect of enhancing students ’ visual selective attention. But that finding is just one small part of a more important message that all parents and educators need to hear: Video games are not the enemy, but the best opportunity we have to engage our kids in real learning.

The objective of this article is to give a tutorial on lattice-based access control models for computer security. The paper begins with a review of Denning's axioms for information flow policies, which provide a theoretical foundation for these models. The structure of security labels

Current standard security practices do not provide substantial assurance that the end-to-end behavior of a computing system satisfies important security policies such as confidentiality. An end-to-end confidentiality policy might assert that secret input data cannot be inferred by an attacker through the attacker's observations of system output; this policy regulates information flow.

pragmatic octions--actions performed to bring one physically closer to a goal-from epistemic actions-actions performed to uncover informatioan that is hidden or hard to compute mentally. To illustrate the need for epistemic actions, we first develop a standard information-processing model of Tetris