In 2016, ALife is presenting a set of keynote presentations whitin a wide variety of topics including cognitive science, robotics, neuroscience, psychology, biology, philosophy, among others.
In 2016, ALife is presenting a set of keynote presentations whitin a wide variety of topics including cognitive science, robotics, neuroscience, psychology, biology, philosophy, among others.
Autopoiesis and Enaction in the Game of Life
Over 40 years ago, the Chilean biologists Humberto Maturana and Francisco Varela put forward the notion of autopoiesis as a way to understand living systems and their phenomenology. Varela and others subsequently extended this framework to an enactive approach that places biological autonomy at the foundation of situated and embodied behavior and cognition. In this talk, I will describe an attempt to place these ideas on a firmer foundation by studying them within the context of a toy model universe, John Conway’s Game of Life (GoL) cellular automata. The talk has both pedagogical and theoretical goals. Simple concrete models provide an excellent vehicle for introducing some of the core concepts of autopoiesis and enaction and explaining how these concepts fit together into a broader whole. In addition, a careful analysis of such toy models can hone our intuitions about these concepts, probe their strengths and weaknesses, and move the entire enterprise in the direction of a more mathematically rigorous theory. In particular, I will identify the primitive processes that can occur in GoL, show how these can be linked together into mutually-supporting networks, map the responses of such entities to environmental perturbations, and investigate the paths of mutual perturbation that these entities and their environments can undergo. Some of the topics that can be examined in GoL include the structure/organization distinction, organizational/operational closure, self-production, self-individuation, destructive vs. nondestructive perturbations, precariousness, cognitive domain, subjectivity, significance, sense-making, structural coupling, and enaction. I will end with some comments on the limitations of the GoL model and directions for future work.
Bio: Randall D. Beer is a professor of cognitive science, computer science, and informatics at Indiana University. His primary research interest is in understanding how coordinated behavior arises from the neurodynamics of an animal’s nervous system, its body and its environment. More generally, he is interested in computational and theoretical biology, including models of metabolism, gene regulation and development. He also has a longstanding interest in the design and implementation of dynamic programming languages and their environments.
Do Endothelial Cells Dream of Eclectic Shape?
Endothelial cells (ECs), which line our blood vessels, exhibit dramatic plasticity and diversity of form/behavior at the individual and collective cell level. They reorganize themselves in space and time to extend new blood vessel networks during development and during a huge array of diseases including cancer. Here we will describe, using examples from our integrated in silico/in vitro/in vivo research program, how the Artificial Life (ALife) perspective and approaches have been paramount in driving entirely new experimental biology understanding of the vasculature by capitalizing on the emergent, predictive capacity and testable nature of agent-based models inclose combination with in vitro and in vivo experiments.
Our agent-based simulations explicitly consider the role of individual EC embodiment, active perception, heterogeneous vs homogeneous collective dynamics, pattern formation and counter-intuitive emergence from feedback in “controller” networks and many more Alife centric concepts. We recently identified in silico that the time it takesECs to collectively decide who should move and who should stay during blood vessel branching morphogenesis can be varied by altering tissue environment conditions, including some changes found in tumors. By proceeding to validate these predictions in vitro and in vivo by integrating the studies in the wetlab we have been able to provide a solid new mechanism to explain the diversity of vascular network structures found across tissues and the malformations arising in disease.
There is a bright future with untapped potential for the Alife community to further contribute to understanding of animals, including humans, at the cell and tissue level, where many organizational principles of the systems behavior are still lacking. If we take care to be rigorous in how we calibrate our models to biological data and make clear experimentally testable predictions, we will show we can make real change in a experimental cell biology field, traditionally segregated from in silico research. Learning from the plight of the insightful, but ostracized, Androids in Philip K Dicks novel, overcoming our cultural differences and integrating better between the artificial and natural living systems research communities could lead to huge advantages in achiev-
ing our common goals to “understand life as it is”.
Bio: Katie Bentley is Assistant Professor of Pathology, Harvard Medical School, she runs an integrated wet and dry lab in the Center for Vascular Biology Research, Beth Israel Deaconess Medical Center, Boston. She is in the process of opening a second interdisciplinary lab at the University of Uppsala, Sweden working closely with a team of vascular biologists. Her focuses include: agent based modeling of collective adaptive behavior, embodiment, morphogenesis, spatiotemporal dynamics of complex systems, predicting mechanisms of vascular growth in health and disease, and importantly, in vitro and in vivo validation of the resulting ALife simulation predictions. She is on the Board of Directors for the International Society of Artificial Life and began her ALife studies with the EASy MSc at Sussex.
Cognition and the Brain
Standard semantic information models are, arguably, conceptually incoherent and factually false about the brain. But, nevertheless, they constitute the primary frameworks for modeling cognitive processes, including in the brain. If such models are ultimately not viable, what sort of framework could model cognition in the brain? I will argue that an action based approach, in the general lineage of pragmatism, provides an alternative modeling framework. In this approach, anticipatory processes are necessary as part of the evolutionary solution to (inter-)action selection, and these yield emergent truth value possibilities of being true or false and thus ground cognition and representation in general. Such an action framework requires timing, thus oscillatory/ modulatory processes, and this is in fact what we find as constituting functional processes in the brain. I will outline a micro-scale level of this model and, if time
permits, a bit of a macro-scale level. This model has some superficial similarities to predictive brain models, but also fundamental and crucial differences.
Bio: Mark Bickhard is the Henry R. Luce Professor in Cognitive Robotics and the Philosophy of Knowledge at Lehigh University. He is affiliated with the Departments of Philosophy and Psychology, and is Director of the Institute for Interactivist Studies. He is Editor of New Ideas in Psychology, Elsevier. His work ranges from process metaphysics and emergence to consciousness, cognition, and language to persons and social ontologies. This work has generated an integrated organization of models encompassing The Whole Person, which is the tentative title of a book in preparation.
Linking Individual to Collective Behavior in Complex Adaptive Networks
A long-standing and central problem in Physics is to understand how collective behavior results from a given two- or N- body fundamental interaction. Similarly, in a society, a central problem is to understand the link between individual social behavior and emergent collective phenomena (vaccination, epidemics, crowd behavior, diffusion of innovations, global governance, etc). Here I address this problem by letting individuals engage in pair-wise interactions by means of a welldefined social dilemma (a prisoner’s dilemma of cooperation). These individuals are embedded in a social network that is both complex and adaptive. Adaptation here allows individuals to manifest preferences and resolve conflicts of interest, reshaping the network accordingly. Exact Monte-Carlo simulations reveal the inadequacy of any of the tools developed to date to predict the co-evolutionary dynamics of the population at large. I will present and discuss in detail an adaptive-network-sensitive observable that is capable of predicting the collective, population-wide dynamics, given prior knowledge of the fundamental rules that govern the social interaction between 2 individuals in a social network. In this fundamental step towards linking individual behavior with population wide dynamics, I show that adaptive social networks act to change the “collective” game, from a 2-person game to a N-person game exhibiting a radically different coevolutionary dynamics, associated with a concomitant fundamental transformation of the nature of the associated Nash equilibria.
Bio: Jorge M. Pacheco (Oporto, 1958) is currently Professor of Mathematics at the Mathematics & Applications Department of the University of Minho (Portugal) and also a member of the Centre of Molecular and Environmental Biology at the same University. His background is in Theoretical Physics, with a degree from the University of Coimbra (Portugal) and a PhD degree from the Niels Bohr Institute, in Copenhagen (Denmark). He is active in a variety of research topics, ranging from many-body physics to the mathematical description of evolutionary processes such as human cancer, evolution of cooperation, urban development, global governance & complexity and complex networks.
Gilbert Simondon and the enactive conception of life and mind
The work of French philosopher Gilbert Simondon is seeing a vigorous rediscovery. His ideas have a richlargely untappedpotential for science, e.g., in origins of life studies, developmental psychology, embodied cognition, and artificial life. I summarise some key concepts of Simondons philosophy side-by-side with ideas in enactivism, an approach to life and mind based on the works of Francisco Varela, Hans Jonas, and Maurice Merleau-Ponty. I hope to show that there is much overlap between the two approaches, which is good, but also many productive complementarities, and some tensions, which is better. Simondon encourages enactivism by making its implications more explicit. He advocates the abandonment of hylomorphic metaphysics (the conceptual separability of form and matter) for an ontology of restless and open-ended materiality, relationality, and virtuality. According to him, being and becoming are mutually co-defined. The subject, in her ongoing individuation, sustains inherently meaningful relations with her world. Physical, biological, mental, and social processes of individuation nicely complement the different kinds of precarious autonomy and sense-making elaborated by enactive theory, concepts that in turn are only implicit in Simondons work. Individuation involves the organization that happens in a milieu capable of abundant potentialities when a process of concrete transduction occurs from more to less metastable states (crystallization is one example). Organisms are processes of individuation prevented from finishing through regulated engagements with the world in search of new sources of potentiality. This coheres with the enactive concept of life as the regulation of the tensions between self-production and self-distinction. Life and mind, for Simondon, entail the neotenic expansion of the early stages of individuation such that its termination is temporarily and progressively delayed. This makes explicit the material conditions of autonomy and introduces new elements for enactivism such as the notion of pre-individual criticality as inherent in the living body. Simondons recurrent use of the term information may entail some tensions with enactivism, although his notion is subtle and different from the (hylomorphic) information processing metaphor of biological or cognitive functionalism. I conclude with reflections on the relevance of Simondons philosophy of technology for artificial life, in particular the implication that any life-like artificial system must be materially embodied and embedded in concrete, open-ended relations with the world.
Bio: Ezequiel A Di Paolo is a full-time Research Professor at Ikerbasque, the Basque Foundation for Science. He also has affiliations with the Centre for Computational Neuroscience and Robotics at the University of Sussex. His work includes research in embodied cognition, dynamical systems, adaptive behaviour in natural and artificial systems, biological modelling, complex systems, evolutionary robotics, and philosophy of science.
Artificial Life and Society: Philosophies and Tools for Experiencing, Interacting with and Managing Real World Complex Adaptive Systems
Many of the grand challenges that society faces are concerned with understanding, managing and indeed creating complex living, lifelike or hybrid systems at multiple scales. Conventional approaches are often unsuccessful in dealing with these complex adaptive systems, which require management tools that interact with dynamic, self-organising processes facing perturbation and change, rather than with inert artefacts. By using interactive steering strategies which exploit CASs dynamics and selforganisation, we can attempt to manoeuvre systems to more preferable, stable states
and update our interventions as they adapt. This however, is not sufficient for real world problem solving. In systems with human involvement, key drivers are often social, political or economic. Possible interventions are limited, goals are subjective and participatory or political processes must be integrated. Not only do we need innovative ways to manage our systems which embrace their complexity, we need broadly-accepted narratives of systems as complex
and adaptive to help us to shape policy and management. We must be prepared to take action with incomplete knowledge and require tools and methodologies for steering, monitoring and learning, allowing us to adapt as systems respond to intervention. All in complex adaptive systems which we for the most part experience and intuit rather than measure. New paradigms are urgently required and our community can play a key role. Artificial Life offers tools and philosophical approaches well-matched to the nature of these systems and can provide important perspectives on how to progress. I will give an overview of the potential contribution that I believe that Alife can make and the need to connect productively with many different disciplines. In particular how ALifes technologies and approaches, combined with its inherent creativity, focus on synthetic methods and philosophy with a screwdriver ethos, provide what I believe is the perfect basis for engaging with real world complex systems.
Bio: Alexandra Penn is a Senior Research Fellow at the University of Surrey working on combining participatory methodologies and mathematical models to create tools for stakeholders to understand and “steer” their complex human ecosystems. She is a principal member of the new “Centre for Evaluating Complexity across the Nexus” a collaboration between academics, policy professionals and the UK government to generate novel, cutting-edge methods for evaluating policy for complex systems. With a background in Artificial Life, Evolutionary Theory, Physics and permaculture design, she has long-standing interests in bringing ideas from diverse domains to innovative applications. She was made a fellow of the Royal Society of Arts for her work in novel application of whole-systems design to bacterial communities and is Chair for Societal Impact of the International Society for Artificial Life.
In symbio biopoiesis as model of evolved Alife (400 PPM Microbiome)
Artificial life techniques are illustrative at exploring the wisdom of natural living systems. Genetic algorithms, cellular automatons are computativily complex and visually seductive with Alife in silico. Robotic artists, creating Alife installations experience design challenges more akin to works created in vivo. Robotic works function both in silico and in vivo, with the virtual spaces of computer code and unpredictable environment of the real world. With robotic Alife installations, things like; will the interactant test the system with muscle or try to defeat the code, are design challenges forcing evolution. Interactive artists have pioneered behavior based works conceived with the current understanding of living systems, such as bottom up emergent behaviors, subsumption architectures (Autopoiesis, Fusiform Polyphony), parallel processing (Paparazzi Bots), distributed intelligences and energy autonomy (400 PPM Microbiome & Autotelematic Spider Bots). Still, in silco / in vivo works within the Alife are islands of artifice. True living systems offer symbiotic convolutions with overlapping living systems at all scales. This is a function of their organic nature. Mitochondria and symbiogenisis are excellent examples. In order for artificial life to further evolve and emerge artists and scientists, will need to create larger symbiotically intertwined systems. Systems moving beyond in silco and in vivo, to in symbio. Prototypical living systems will need to find and collect their own energy sources from both living and non living systems. They will find symbiotic intwining through organic interfaces to complex social systems (Augmented Fish Reality) and to bacterial cultures (Enteric Consciousness). Alife research that pioneers natural organic breakdown with bacterial cultures and sustainable practices such as aquaponics offer clear examples (The Farm Fountain). In Symbio intertwinings of natural and inorganic electro-mechanical elements will be an important and very natural confluence and co-evolution that is necessary between living and co-evolving technological cultures, in the future of Alife.
Bio: Ken Rinaldo is internationally recognized for his interactive installations blurring the boundaries between the organic and inorganic and speaking to the co-evolution between living and evolving technological cultures. His work interrogates fuzzy boundaries where hybrids arise. Biological, machine and algorithmic species and their unique intelligences are mixing in unexpected ways and we need to better understand the complex intertwined ecologies that these semi-living species create. Rinaldo is focused on trans-species communication and researching methods to understand animal, insect and bacterial cultures as models for emergent machine intelligences, as they interact, self organize and co-inhabit the earth.
Climate Change Governance, Cooperation and Self-organization
When attempting to avoid global warming, individuals often face a social dilemma in which, besides securing future benefits, it is also necessary to reduce the chances of future losses. Unfortunately, individuals, regions or nations may opt to be “free riders”, hoping to benefit from the efforts of others while choosing not to make any effort themselves. Moreover, nations and their leaders seek a collective goal that is shadowed by the uncertainty of its achievement. Such types of uncertainties have repeatedly happened throughout human history from group hunting to voluntary adoption of public health measures and other prospective choices. In this talk, I will discuss a population dynamics approach to a broad class of cooperation problems in which attempting to minimize future losses turns the risk of failure into a central issue in individual decisions. Our results suggest that global coordination for a common good should be attempted by segmenting tasks in many small to medium sized groups in which perception of risk is high. Moreover, whenever the perception of risk is low — as it is presently the case — we find that a polycentric approach involving multiple institutions is more effective than that associated with a single, global one, indicating that a bottom-up approach, setup at a local scale, provides a better ground on which to attempt a solution for such a complex and global dilemma. Finally, I will discuss the impact on public goods dilemmas of uncertainty in collective goals, heterogeneous political networks, obstinate players and wealth inequality, including a distribution of wealth representative of existing inequalities among nations.
Bio: Francisco C. Santos is an Assistant Professor of the Department of Computer Science and Engineering of Instituto Superior Técnico (IST), University of Lisbon (Portugal). He is a researcher of GAIPS, a research group part of INESC-ID, and a member of the ATP group, hosted by the Institute for Interdiciplinary Research of the University of Lisbon. His research interests span several aspects of complex systems, from cultural evolution and dynamics of human cooperation to networks science.
Why development matters to (artificial) life: Lessons from human babies
Why do living forms develop? Development, like evolution and culture, is a process that creates complexity by accumulating change. At any moment, the developing agent is a product of all previous developments, and any new change begins with and must build on those previous developments. Biological systems that are flexibly smart have relatively long periods of immaturity. Why is this? This talk will consider answers to this question using evidence from the first two years of life of human infants. The core ideas are that an adaptive system that can succeed in varied and novel contexts is slow does not settle too fast; develops new mechanisms of change and learning processes over the life time; develops in a series of different environments.
Bio: Distinguished Professor and Chancellor’s Professor of Psychological and Brain Sciences. Her central theoretical question is the study of developmental process and mechanisms of change. Her work focuses on early changes in perception, language, and action and how those changes in these areas support each other particularly around the age (12 months to 24 months) that children break into language. The research takes a systems approach, seeking to understand how multiple components interact over nested time scales and levels of analysis and how, in so doing, they yield an individual’s developmental path.