ALife XV provides a venue for a number of satellite workshops, which are run and administered independently from the main conference. If you are interested in participating in one of the workshops, please visit the relevant website below. For workshops that do not currently have a website, please contact the workshop organiser for more details.
Often, research done by scientists in one field can take a long time to percolate to scientists in another field. This is especially true in Biology and Computer Science, even with closely related sub-fields such as evolutionary computation and evolutionary biology. Such delays can substantially slow down scientific discovery, leading to the premium that many funding agencies have placed on research that cuts across disciplines. More info and submissions.
New technologies that exploit or emulate the unique properties of living systems have great potential, but the non-linearity and complexity exhibited by these systems render “brute force” approaches to control insufficient. An emerging collection of approaches use “steering”, whereby we continually interact with systems and attempt to move them between attractors — from biofilm evolution to bio-hybrid societies to industrial networks. The workshop aims to bring together researchers interested in understanding and modulating complex biological and societal systems, to discuss various perspectives on methods, ethics, and conceptual issues as well as real-world and experimental example systems. More info and submissions.
The workshop will consist of a half day of presentations and will consist of two parts. The first half of this workshop aims to provide an interdisciplinary overview of the fields of social learning and cultural evolution. By doing this we hope to extend the scope of research in the social learning ALife community to incorporate more interdisciplinary concepts and provide a firm basis for interdisciplinary discussion and collaboration. More info and submissions.
Enactivism has become a successful component of cognitive science, but at its heart it is also a theory of biology. The workshop will bring together researchers in enactive cognition, computational modeling, biology and philosophy to revisit the biological foundations of enactivism, and in particular the question of how key concepts such as operational closure and adaptivity can be grounded. Of particular interest are topics relating to the origins of life. More info and submissions.
The goal of the OEE2 workshop is to build upon the outcomes of OEE1 by discussing recent progress on the following key issues: (1) Behavioral hallmarks of systems undergoing OEE; (2) Hypothesized requirements (mechanisms) for systems to undergo OEE; and (3) Empirical demonstrations of hallmarks or requirements of OEE in models or natural systems. The workshop will emphasize precise, operational, quantitative, empirical definitions of hallmarks and requirements for OEE, and will also encourage critical reflections about all these topics.. More info and submissions.
The goal of Guided Self-Organization (GSO) is to leverage the strengths of self-organization (simplicity, parallelization, adaptability, robustness, scalability) while still being able to direct the outcome of the self-organizing process. GSO typically has the following features: (i) an increase in organization (structure and/or functionality) over some time; (ii) the local interactions are not explicitly guided by any external agent; (iii) task-independent objectives are combined with task-dependent constraints. More info and submissions.
This workshop aims to promote and expand Morphogenetic Engineering, a recent field of research exploring the artificial design and implementation of autonomous systems capable of developing complex, heterogeneous morphologies (e.g. inspired by multicellular development and insect constructions). Particular emphasis is set on the programmability and computing abilities of self-organization, properties that are often underappreciated in complex systems science–while, conversely, the benefits of self-organization are often underappreciated in engineering methodologies. More info and submissions.
Evolutionary game theory joins mathematical concepts of classical game theory with evolutionary principals from biology. The method has been shown to be very fruitful in modelling systems in many different fields, from biology to economy and sociology. Its success lies in two facts: it does not need the assumption of rationality and its solutions offer the whole dynamics of the system, not just its equilibria. More info and submissions.