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“Artificial Life”
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By default, Find returns all publications that contain the words in the surnames of their author, in their titles, or in their years. For example,
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Agmon E., Gates A. J., Churavy V. & Beer R. D. (2016) Exploring the space of viable configurations in a model of metabolism–boundary co-construction. Artificial Life 22(2): 153–171.
Agmon E.
,
Gates A. J.
,
Churavy V.
&
Beer R. D.
(
2016
)
Exploring the space of viable configurations in a model of metabolism–boundary co-construction
.
Artificial Life
22(2): 153–171.
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We introduce a spatial model of concentration dynamics that supports the emergence of spatiotemporal inhomogeneities that engage in metabolism–boundary co-construction. These configurations exhibit disintegration following some perturbations, and self-repair in response to others. We define robustness as a viable configuration’s tendency to return to its prior configuration in response to perturbations, and plasticity as a viable configuration’s tendency to change to other viable configurations. These properties are demonstrated and quantified in the model, allowing us to map a space of viable configurations and their possible transitions. Combining robustness and plasticity provides a measure of viability as the average expected survival time under ongoing perturbation, and allows us to measure how viability is affected as the configuration undergoes transitions. The framework introduced here is independent of the specific model we used, and is applicable for quantifying robustness, plasticity, and viability in any computational model of
artificial life
that demonstrates the conditions for viability that we promote.
Key words:
autopoiesis
,
viability
,
robustness
,
plasticity
,
spatial dynamical system
,
metabolism
Aguayo C. (2019) Autopoiesis in digital learning design: Theoretical implications in education. In: Proceedings of the 2019 Conference on Artificial Life (ALIFE 2019). MIT Press, Cambridge MA: 495–496. https://cepa.info/8142
Aguayo C.
(
2019
)
Autopoiesis in digital learning design: Theoretical implications in education
.
In:
Proceedings of the 2019 Conference on
Artificial Life
(ALIFE 2019)
. MIT Press, Cambridge MA: 495–496.
Fulltext at https://cepa.info/8142
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Today’s mobile and smart technologies have a key role to play in the transformative potential of educational practice. However, technology-enhanced learning processes are embedded within an inherent and unpredictable complexity, not only in the design and development of educational experiences, but also within the socio-cultural and technological contexts where users and learners reside. This represents a limitation with current mainstream digital educational practice, as digital experiences tend to be designed and developed as ‘one solution fits all’ products, and/or as ‘one-off’ events, failing to address ongoing socio-technological complexity, therefore tending to decay in meaningfulness and effectiveness over time. One ambitious solution is to confer the processes associated with the design and development of digital learning experiences with similar autopoietic properties found within living systems, in particular adaptability and self-organisation. The underpinning rationale is that, by conferring such properties to digital learning experiences, intelligent digital interventions responding to unpredictable and ever-changing socio-cultural conditions can be created, promoting meaningful learning over-time. Such an epistemological view of digital learning aims to ultimately promote a more efficient type of design and development of digital learning experiences in education. Read less
Barandiaran X. E. (2004) Behavioral adaptive autonomy. A milestone on the Alife route to AI. In: Pollack J., Bedau M. A., Husbands P., Ikegami T. & Watson R. A. (eds.) Artificial life IX: Proceedings of the ninth international conference on the simulation and synthesis of artificial life. MIT Press, Cambridge: 514–521.
Barandiaran X. E.
(
2004
)
Behavioral adaptive autonomy. A milestone on the Alife route to AI
.
In: Pollack J., Bedau M. A., Husbands P., Ikegami T. & Watson R. A. (eds.)
Artificial life
IX: Proceedings of the ninth international conference on the simulation and synthesis of
artificial life
. MIT Press, Cambridge: 514–521.
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Barandiaran X. E. & Egbert M. (2013) Norm-establishing and norm-following in autonomous agency. Artificial Life 20(1): 5–28. https://cepa.info/6554
Barandiaran X. E.
&
Egbert M.
(
2013
)
Norm-establishing and norm-following in autonomous agency
.
Artificial Life
20(1): 5–28.
Fulltext at https://cepa.info/6554
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Living agency is subject to a normative dimension (good-bad, adaptive-maladaptive) that is absent from other types of interaction. We review current and historical attempts to naturalize normativity from an organism-centered perspective, identifying two central problems and their solution: (1) How to define the topology of the viability space so as to include a sense of gradation that permits reversible failure, and (2) how to relate both the processes that establish norms and those that result in norm-following behavior. We present a minimal metabolic system that is coupled to a gradient-climbing chemotactic mechanism. Studying the relationship between metabolic dynamics and environmental resource conditions, we identify an emergent viable region and a precarious region where the system tends to die unless environmental conditions change. We introduce the concept of normative field as the change of environmental conditions required to bring the system back to its viable region. Norm-following, or normative action, is defined as the course of behavior whose effect is positively correlated with the normative field. We close with a discussion of the limitations and extensions of our model and some final reflections on the nature of norms and teleology in agency.
Barandiaran X. E. & Moreno A. (2006) ALife models as epistemic artefacts. In: Rocha L., Yaeger L., Bedau M., Floreano D., Goldstone R. & Vespignani A. (eds.) Artificial life X.: Proceedings of the tenth international conference on the simulation and synthesis of living systems. MIT Press, Cambridge: 513–519.
Barandiaran X. E.
&
Moreno A.
(
2006
)
ALife models as epistemic artefacts
.
In: Rocha L., Yaeger L., Bedau M., Floreano D., Goldstone R. & Vespignani A. (eds.)
Artificial life
X.: Proceedings of the tenth international conference on the simulation and synthesis of living systems
. MIT Press, Cambridge: 513–519.
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Beer R. (2004) Autopoiesis and cognition in the game of life. Artificial Life 10: 309–326. https://cepa.info/1143
Beer R.
(
2004
)
Autopoiesis and cognition in the game of life
.
Artificial Life
10: 309–326.
Fulltext at https://cepa.info/1143
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Maturana and Varela’s notion of autopoiesis has the potential to transform the conceptual foundation of biology as well as the cognitive, behavioral, and brain sciences. In order to fully realize this potential, however, the concept of autopoiesis and its many consequences require significant further theoretical and empirical development. A crucial step in this direction is the formulation and analysis of models of autopoietic systems. This article sketches the beginnings of such a project by examining a glider from Conway’s game of life in autopoietic terms. Such analyses can clarify some of the key ideas underlying autopoiesis and draw attention to some of the central open issues. This article also examines the relationship between an autopoietic perspective on cognition and recent work on dynamical approaches to the behavior and cognition of situated, embodied agents.
Relevance:
The article focuses on the theory of autopoiesis and related concepts such as structural coupling and cognitive domain.
Beer R. D. (2014) The cognitive domain of a glider in the Game of Life. Artificial Life 20: 183–206. https://cepa.info/6303
Beer R. D.
(
2014
)
The cognitive domain of a glider in the Game of Life
.
Artificial Life
20: 183–206.
Fulltext at https://cepa.info/6303
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This article examines in some technical detail the application of Maturana and Varela’s biology of cognition to a simple concrete model: a glider in the game of Life cellular automaton. By adopting an autopoietic perspective on a glider, the set of possible perturbations to it can be divided into destructive and nondestructive subsets. From a glider’s reaction to each nondestructive perturbation, its cognitive domain is then mapped. In addition, the structure of a glider’s possible knowledge of its immediate environment, and the way in which that knowledge is grounded in its constitution, are fully described. The notion of structural coupling is then explored by characterizing the paths of mutual perturbation that a glider and its environment can undergo. Finally, a simple example of a communicative interaction between two gliders is given. The article concludes with a discussion of the potential implications of this analysis for the enactive approach to cognition.
Key words:
autopoiesis
,
enaction
,
cognitive domain
,
structural coupling
,
cellular automata.
Beer R. D. (2015) Characterizing autopoiesis in the game of life. Artificial Life 21: 1–19. https://cepa.info/1213
Beer R. D.
(
2015
)
Characterizing autopoiesis in the game of life
.
Artificial Life
21: 1–19.
Fulltext at https://cepa.info/1213
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Maturana and Varela’s concept of autopoiesis defines the essential organization of living systems and serves as a foundation for their biology of cognition and the enactive approach to cognitive science. As an initial step toward a more formal analysis of autopoiesis, this paper investigates its application to the compact, recurrent spatiotemporal patterns that arise in Conway’s Game of Life cellular automata. In particular, we demonstrate how such entities can be formulated as self-constructing networks of interdependent processes that maintain their own boundaries. We then characterize the specific organizations of several such entities, suggest a way to simplify the descriptions of these organizations, and briefly consider the transformation of such organizations over time.
Relevance:
The paper presents an analysis of a minimal concrete model of autopoiesis to provide a more rigorous foundation for the concept of autopoiesis and highlight its ambiguities and difficulties.
Beer R. D. (2018) On the origin of gliders. In: Ikegami T., Virgo N., Witkowski O., Oka M., Suzuk R. & Iizuka H. (eds.) Proceedings of the 2018 Conference on Artificial Life. MIT Press, Cambridge MA: 67–74. https://cepa.info/6304
Beer R. D.
(
2018
)
On the origin of gliders
.
In: Ikegami T., Virgo N., Witkowski O., Oka M., Suzuk R. & Iizuka H. (eds.)
Proceedings of the 2018 Conference on
Artificial Life
. MIT Press, Cambridge MA: 67–74.
Fulltext at https://cepa.info/6304
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Using a glider in the Game of Life cellular automaton as a toy model, we explore how questions of origins might be approached from the perspective of autopoiesis. Specifically, we examine how the density of gliders evolves over time from random initial conditions and then develop a statistical mechanics of gliders that explains this time evolution in terms of the processes of glider creation, persistence and destruction that underlie it.
Beer R. D. (2020) An integrated perspective on the constitutive and interactive dimensions of autonomy. In: Bongard J., Lovato J., Soros L. & Hebert-Dufrésne L. (eds.) Proceedings of the 2020 Conference on Artificial Life (ALIFE 2020). MIT Press, Cambridge MA: 202–209. https://cepa.info/7618
Beer R. D.
(
2020
)
An integrated perspective on the constitutive and interactive dimensions of autonomy
.
In: Bongard J., Lovato J., Soros L. & Hebert-Dufrésne L. (eds.)
Proceedings of the 2020 Conference on
Artificial Life
(ALIFE 2020)
. MIT Press, Cambridge MA: 202–209.
Fulltext at https://cepa.info/7618
Copy Citation
Enaction’s claim of continuity between life and mind is a bold one. We investigate one aspect of this claim using a glider in the Game of Life as a toy model. Specifically, we study the relationship between theories of glider constitution and glider interaction, demonstrating how a glider’s constitution completely determines its interaction graph, but not the particular life that it enacts, which also requires knowledge of the dynamics of its environment.
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