1,776 research outputs found
Artificial life meets computational creativity?
I review the history of work in Artificial Life on the problem of the open-ended evolutionary growth of complexity in computational worlds. This is then put into the context of evolutionary epistemology and human creativity
Discovering Evolutionary Stepping Stones through Behavior Domination
Behavior domination is proposed as a tool for understanding and harnessing
the power of evolutionary systems to discover and exploit useful stepping
stones. Novelty search has shown promise in overcoming deception by collecting
diverse stepping stones, and several algorithms have been proposed that combine
novelty with a more traditional fitness measure to refocus search and help
novelty search scale to more complex domains. However, combinations of novelty
and fitness do not necessarily preserve the stepping stone discovery that
novelty search affords. In several existing methods, competition between
solutions can lead to an unintended loss of diversity. Behavior domination
defines a class of algorithms that avoid this problem, while inheriting
theoretical guarantees from multiobjective optimization. Several existing
algorithms are shown to be in this class, and a new algorithm is introduced
based on fast non-dominated sorting. Experimental results show that this
algorithm outperforms existing approaches in domains that contain useful
stepping stones, and its advantage is sustained with scale. The conclusion is
that behavior domination can help illuminate the complex dynamics of
behavior-driven search, and can thus lead to the design of more scalable and
robust algorithms.Comment: To Appear in Proceedings of the Genetic and Evolutionary Computation
Conference (GECCO 2017
Computational Social Creativity
This article reviews the development of computational models of creativity where social interactions are central. We refer to this area as computational social creativity. Its context is described, including the broader study of creativity, the computational modeling of other social phenomena, and computational models of individual creativity. Computational modeling has been applied to a number of areas of social creativity and has the potential to contribute to our understanding of creativity. A number of requirements for computational models of social creativity are common in artificial life and computational social science simulations. Three key themes are identified: (1) computational social creativity research has a critical role to play in understanding creativity as a social phenomenon and advancing computational creativity by making clear epistemological contributions in ways that would be challenging for other approaches; (2) the methodologies developed in artificial life and computational social science carry over directly to computational social creativity; and (3) the combination of computational social creativity with individual models of creativity presents significant opportunities and poses interesting challenges for the development of integrated models of creativity that have yet to be realized
Past Visions of Artificial Futures: One Hundred and Fifty Years under the Spectre of Evolving Machines
The influence of Artificial Intelligence (AI) and Artificial Life (ALife)
technologies upon society, and their potential to fundamentally shape the
future evolution of humankind, are topics very much at the forefront of current
scientific, governmental and public debate. While these might seem like very
modern concerns, they have a long history that is often disregarded in
contemporary discourse. Insofar as current debates do acknowledge the history
of these ideas, they rarely look back further than the origin of the modern
digital computer age in the 1940s-50s. In this paper we explore the earlier
history of these concepts. We focus in particular on the idea of
self-reproducing and evolving machines, and potential implications for our own
species. We show that discussion of these topics arose in the 1860s, within a
decade of the publication of Darwin's The Origin of Species, and attracted
increasing interest from scientists, novelists and the general public in the
early 1900s. After introducing the relevant work from this period, we
categorise the various visions presented by these authors of the future
implications of evolving machines for humanity. We suggest that current debates
on the co-evolution of society and technology can be enriched by a proper
appreciation of the long history of the ideas involved.Comment: To appear in Proceedings of the Artificial Life Conference 2018
(ALIFE 2018), MIT Pres
WebAL Comes of Age: A review of the first 21 years of Artificial Life on the Web
We present a survey of the first 21 years of web-based artificial life (WebAL) research and applications, broadly construed to include the many different ways in which artificial life and web technologies might intersect. Our survey covers the period from 1994āwhen the first WebAL work appearedāup to the present day, together with a brief discussion of relevant precursors. We examine recent projects, from 2010ā2015, in greater detail in order to highlight the current state of the art. We follow the survey with a discussion of common themes and methodologies that can be observed in recent work and identify a number of likely directions for future work in this exciting area
Necessary Conditions for Open-Ended Evolution
Evolution on Earth is widely considered to be an effectively endless process. Though this phenomenon of open-ended evolution (OEE) has been a topic of interest in the artificial life community since its beginnings, the field still lacks an empirically validated theory of what exactly is necessary to reproduce the phenomenon in general (including in domains quite unlike Earth). This dissertation (1) enumerates a set of conditions hypothesized to be necessary for OEE in addition to (2) introducing an artificial life world called Chromaria that incorporates each of the hypothesized necessary conditions. It then (3) describes a set of experiments with Chromaria designed to empirically validate the hypothesized necessary conditions. Thus, this dissertation describes the first scientific endeavor to systematically test an OEE framework in an alife world and thereby make progress towards solving an open question not just for evolutionary computation and artificial life, but for science in general
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