119,613 research outputs found
Fundamental Laws and Assumptions of Software Maintenance
Researchers must pay far more attention to discovering and validating the
principles that underlie software maintenance and evolution. This was one
of the major conclusions reached during the International Workshop on
Empirical Studies of Software Maintenance. This workship, held in
November 1996 in Monterey, California, brought together an international
group of researchers to discuss the successes, challenges and open issues
in software maintenance and evolution.
This article documents the discussion of the subgroup on fundamental laws
and assumption of software maintenance. The participants of this group in
included researchers in software engineering, the behavioral sciences,
information systems and statistics. Their main conclusion was that
insufficient effort has been paid to synthesizing research conjectures
into validated theories and this problem has slowed progress in software
maintenance. To help remedy this situation they made the following
recommendations: (1) when we use empirical methods, an explicit goal
should be to develop theories, (2) we should look to other disciplines
for help where it is appropriate, and (3) our studies should use a wider
range of empirical methods
(Also cross-referenced as UMIACS-TR-97-21
Mathematics Is Physics
In this essay, I argue that mathematics is a natural science---just like
physics, chemistry, or biology---and that this can explain the alleged
"unreasonable" effectiveness of mathematics in the physical sciences. The main
challenge for this view is to explain how mathematical theories can become
increasingly abstract and develop their own internal structure, whilst still
maintaining an appropriate empirical tether that can explain their later use in
physics. In order to address this, I offer a theory of mathematical
theory-building based on the idea that human knowledge has the structure of a
scale-free network and that abstract mathematical theories arise from a
repeated process of replacing strong analogies with new hubs in this network.
This allows mathematics to be seen as the study of regularities, within
regularities, within ..., within regularities of the natural world. Since
mathematical theories are derived from the natural world, albeit at a much
higher level of abstraction than most other scientific theories, it should come
as no surprise that they so often show up in physics.
This version of the essay contains an addendum responding to Slyvia
Wenmackers' essay and comments that were made on the FQXi website.Comment: 15 pages, LaTeX. Second prize winner in 2015 FQXi Essay Contest (see
http://fqxi.org/community/forum/topic/2364
Can models of agents be transferred between different areas?
One of the main reasons for the sustained activity and interest in the field of agent-based systems, apart from the obvious recognition of its value as a natural and intuitive way of understanding the world, is its reach into very many different and distinct fields of investigation. Indeed, the notions of agents and multi-agent systems are relevant to fields ranging from economics to robotics, in contributing to the foundations of the field, being influenced by ongoing research, and in providing many domains of application. While these various disciplines constitute a rich and diverse environment for agent research, the way in which they may have been linked by it is a much less considered issue. The purpose of this panel was to examine just this concern, in the relationships between different areas that have resulted from agent research. Informed by the experience of the participants in the areas of robotics, social simulation, economics, computer science and artificial intelligence, the discussion was lively and sometimes heated
Joint perceptual decision-making: a case study in explanatory pluralism.
Traditionally different approaches to the study of cognition have been viewed as competing explanatory frameworks. An alternative view, explanatory pluralism, regards different approaches to the study of cognition as complementary ways of studying the same phenomenon, at specific temporal and spatial scales, using appropriate methodological tools. Explanatory pluralism has been often described abstractly, but has rarely been applied to concrete cases. We present a case study of explanatory pluralism. We discuss three separate ways of studying the same phenomenon: a perceptual decision-making task (Bahrami et al., 2010), where pairs of subjects share information to jointly individuate an oddball stimulus among a set of distractors. Each approach analyzed the same corpus but targeted different units of analysis at different levels of description: decision-making at the behavioral level, confidence sharing at the linguistic level, and acoustic energy at the physical level. We discuss the utility of explanatory pluralism for describing this complex, multiscale phenomenon, show ways in which this case study sheds new light on the concept of pluralism, and highlight good practices to critically assess and complement approaches
Towards Good Social Science
The paper investigates what is meant by "good science" and "bad science" and how these differ as between the natural (physical and biological) sciences on the one hand and social sciences on the other. We conclude on the basis of historical evidence that the natural science are much more heavily constrained by evidence and observation than by theory while the social sciences are constrained by prior theory and hardly at all by direct evidence. Current examples of the latter proposition are taken from recent issues of leading social science journals. We argue that agent based social simulations can be used as a tool to constrain the development of a new social science by direct (what economists dismiss as anecdotal) evidence and that to do so would make social science relevant to the understanding and influencing of social processes. We argue that such a development is both possible and desirable. We do not argue that it is likely.Methodology, Agent Based Social Simulation, Qualitative Analysis; Evidence; Conditions of Application; History of Science
From Models to Simulations
This book analyses the impact computerization has had on contemporary science and explains the origins, technical nature and epistemological consequences of the current decisive interplay between technology and science: an intertwining of formalism, computation, data acquisition, data and visualization and how these factors have led to the spread of simulation models since the 1950s.
Using historical, comparative and interpretative case studies from a range of disciplines, with a particular emphasis on the case of plant studies, the author shows how and why computers, data treatment devices and programming languages have occasioned a gradual but irresistible and massive shift from mathematical models to computer simulations
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