353 research outputs found
Measuring autonomy and emergence via Granger causality
Concepts of emergence and autonomy are central to artificial life and related cognitive and behavioral sciences. However, quantitative and easy-to-apply measures of these phenomena are mostly lacking. Here, I describe quantitative and practicable measures for both autonomy and emergence, based on the framework of multivariate autoregression and specifically Granger causality. G-autonomy measures the extent to which the knowing the past of a variable helps predict its future, as compared to predictions based on past states of external (environmental) variables. G-emergence measures the extent to which a process is both dependent upon and autonomous from its underlying causal factors. These measures are validated by application to agent-based models of predation (for autonomy) and flocking (for emergence). In the former, evolutionary adaptation enhances autonomy; the latter model illustrates not only emergence but also downward causation. I end with a discussion of relations among autonomy, emergence, and consciousness
A Functional Naturalism
I provide two arguments against value-free naturalism. Both are based on considerations concerning biological teleology. Value-free naturalism is the thesis that both (1) everything is, at least in principle, under the purview of the sciences and (2) all scientific facts are purely non-evaluative. First, I advance a counterexample to any analysis on which natural selection is necessary to biological teleology. This should concern the value-free naturalist, since most value-free analyses of biological teleology appeal to natural selection. My counterexample is unique in that it is likely to actually occur. It concerns the creation of synthetic life. Recent developments in synthetic biology suggest scientists will eventually be able to develop synthetic life. Such life, however, would not have any of its traits naturally selected for. Second, I develop a simple argument that biological teleology is a scientific but value-laden notion. Consequently, value-free naturalism is false. I end with some concluding remarks on the implications for naturalism, the thesis that (1). Naturalism may be salvaged only if we reject (2). (2) is a dogma that unnecessarily constrains our conception of the sciences. Only a naturalism that recognizes value-laden notions as scientifically respectable can be true. Such a naturalism is a functional naturalism
The view from elsewhere: perspectives on ALife Modeling
Many artificial life researchers stress the interdisciplinary character of the field. Against such a backdrop, this report reviews and discusses artificial life, as it is depicted in, and as it interfaces with, adjacent disciplines (in particular, philosophy, biology, and linguistics), and in the light of a specific historical example of interdisciplinary research (namely cybernetics) with which artificial life shares many features. This report grew out of a workshop held at the Sixth European Conference on Artificial Life in Prague and features individual contributions from the workshop's eight speakers, plus a section designed to reflect the debates that took place during the workshop's discussion sessions. The major theme that emerged during these sessions was the identity and status of artificial life as a scientific endeavor
The Implications of Interactions for Science and Philosophy
Reductionism has dominated science and philosophy for centuries. Complexity
has recently shown that interactions---which reductionism neglects---are
relevant for understanding phenomena. When interactions are considered,
reductionism becomes limited in several aspects. In this paper, I argue that
interactions imply non-reductionism, non-materialism, non-predictability,
non-Platonism, and non-nihilism. As alternatives to each of these, holism,
informism, adaptation, contextuality, and meaningfulness are put forward,
respectively. A worldview that includes interactions not only describes better
our world, but can help to solve many open scientific, philosophical, and
social problems caused by implications of reductionism.Comment: 12 pages, 2 figure
Multivariate Granger Causality and Generalized Variance
Granger causality analysis is a popular method for inference on directed
interactions in complex systems of many variables. A shortcoming of the
standard framework for Granger causality is that it only allows for examination
of interactions between single (univariate) variables within a system, perhaps
conditioned on other variables. However, interactions do not necessarily take
place between single variables, but may occur among groups, or "ensembles", of
variables. In this study we establish a principled framework for Granger
causality in the context of causal interactions among two or more multivariate
sets of variables. Building on Geweke's seminal 1982 work, we offer new
justifications for one particular form of multivariate Granger causality based
on the generalized variances of residual errors. Taken together, our results
support a comprehensive and theoretically consistent extension of Granger
causality to the multivariate case. Treated individually, they highlight
several specific advantages of the generalized variance measure, which we
illustrate using applications in neuroscience as an example. We further show
how the measure can be used to define "partial" Granger causality in the
multivariate context and we also motivate reformulations of "causal density"
and "Granger autonomy". Our results are directly applicable to experimental
data and promise to reveal new types of functional relations in complex
systems, neural and otherwise.Comment: added 1 reference, minor change to discussion, typos corrected; 28
pages, 3 figures, 1 table, LaTe
Topology and Evolution of Technology Innovation Networks
The web of relations linking technological innovation can be fairly described
in terms of patent citations. The resulting patent citation network provides a
picture of the large-scale organization of innovations and its time evolution.
Here we study the patterns of change of patents registered by the US Patent and
Trademark Office (USPTO). We show that the scaling behavior exhibited by this
network is consistent with a preferential attachment mechanism together with a
Weibull-shaped aging term. Such attachment kernel is shared by scientific
citation networks, thus indicating an universal type of mechanism linking ideas
and designs and their evolution. The implications for evolutionary theory of
innovation are discussed.Comment: 6 pages, 5 figures, submitted to Physical Review
Reduction and Emergence in Bose-Einstein Condensates
A closer look at some proposed Gedanken-experiments on BECs promises to shed
light on several aspects of reduction and emergence in physics. These include
the relations between classical descriptions and different quantum treatments
of macroscopic systems, and the emergence of new properties and even new
objects as a result of spontaneous symmetry breaking
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