Special Sessions

Similarly to past ALife and ECAL conferences, ALIFE 2018 will be composed of a number of sessions, whose topics will be determined by the submissions. However there will also be a number of special sessions, organised by members of the Artificial Life community to increase engagement in particular topics. These sessions share the same review system as the main conference tracks, and accepted submissions will be published in the proceedings.

The special sessions are listed below. To submit to a special session, follow the instructions for authors and select your session when prompted. Please feel free to contact the session organisers directly for more details about a session.

Special sessions are distinct from workshops, which are organised separately from the main conference. Workshops will be announced at a later date. (To propose a workshop, see the workshops page.)

List of Sessions (click for more details)

  • ALife and Society: Transcending the artificial-natural divide
  • Hybrid life: Approaches to integrate biological, artificial and cognitive systems
  • Machine Learning in ALife
  • Morphogenetic Engineering

ALife and Society: Transcending the artificial-natural divide

Organisers: Alex Penn and J. Mario Siqueiros

As part of an ALife conference with Beyond AI as its central theme, this session will focus on
how technology in general, and AI in particular are creating new, complex adaptive, possibly
living or cognitive, systems, new modes of being and interaction, and new contexts for
evolution and evolutionary dynamics as well as modifying existing ones. All of these
“transcending the natural-artificial divide”.
The history of human society is of ongoing creation of, and co-evolution and interaction with
complex adaptive systems at larger and larger scales. Much of this has involved processes
of incorporating our environment into new, extended human systems, and modifying our
environment in ways that feed back onto our evolution. The origin of art, of agriculture and
the industrial revolution for example, all created explosions of new, interdependent
ecological, biological, social and cultural niches and dynamics which profoundly changed
both our ways of living, our evolutionary possibilities and what constituted our extended
human systems rather than our environment.

ALife now goes beyond the classic categories of wet, hard and soft. ALife is now out there
in the real world and it is with us as we are with it. The boundaries are diffuse but as
traditional limits seem to disappear, new identities, new forms of autonomy and new
biospheres are emerging. This requires governance and guidance of the Artificial Life that
is shaping ourselves, society and the whole planet, identifying new societal and individual
responsibilities, and understanding the ongoing construction of bio-socio- tech-
environmental interdependencies.

A case worthy of consideration is the emergence of the Internet and the Web which have
provided new possibilities for system creation and interconnection, communication and
understanding and provide new contexts and feedbacks for our evolution and new possible
extensions to how human systems can exist or be defined. As Artificial Intelligence (AI)
becomes present in almost every aspect of human life, this is a crucial time to address
these themes.

This session aims to focus on consideration of the implications of socio-ecological-
technological systems as hybrid living systems with some forms of artificial life and
intelligence in their own right. And on our dynamic creation of, and interconnectedness,
interactions and co-evolution with these systems. We will create a space for discussing the
theoretical questions, modeling strategies and ethical issues that revolve around the
dynamics of the co-evolution of the self, society, biosphere and technology and of the
emergence of properties of lifelike and cognitive systems at new, higher, levels.

Potential speakers are invited to submit abstracts or papers on the session themes via the
Alife 2018 website. Speakers are encouraged to present new and exploratory ideas, to
suggest new disciplinary connections and to pose novel questions. The session will take
the form of short talks followed by interactive group discussion. Key themes, debates and
ideas from the session will form the basis of a collaborative piece for the Societal Impact
Section of the MIT Press Journal of Artificial Life to which speakers will be invited to

Topics of Interest Include (but are not limited to):

  • Removing the Natural-Artificial Divide: socio-ecological-technical systems as hybrid living systems
  • Co-evolution of the self, society, biosphere and technology
  • Artificial Life in the Anthropocene: Philosophical and practical approaches to ubiquitous Artificial Life
  • Societal implications of living, hybrid and lifelike technologies and artifacts and technologies with agency
  • Technical, philosophical and social implications of synthetic ecology, living and life-like technology and bio-hybrid societies and systems
  • Impact of emerging living and intelligent technologies on society
  • Developing novel institutions for managing multi-level living and intelligent systems
  • Ethical and societal issues in manipulating complex and large-scale living/cognitive hybrid systems
  • Conceptual, philosophical and technical issues in managing complex, living or life-like Societal systems – key challenges, opportunities and methodologies
  • Emergent interactions and dynamic aspects of the organism-environment boundary in socio-ecological-technical systems
  • Visions of artificial futures. ALife-inspired visions and fiction for the Anthropocene

Hybrid Life: Approaches to integrate biological, artificial and cognitive systems

Organisers: Manuel Baltieri (, Keisuke Suzuki and Hiroyuki Iizuka
Web page:

The main focus of ALife research is the study of natural systems with the goal of understanding what life is. More concretely, ALife defines ways to investigate processes that contribute to the formation and proliferation of living organisms. In this session we focus on three common approaches to tackle this investigation, proposing ways to integrate, extend and possibly improve them. More specifically we refer to: 1) the formalisation of the necessary properties for the definition of life, 2) the implementation of artificial agents, and 3) the study of the relation between life and cognition.

For this special session we propose to start from these well-established Alife methodologies, and extend them through:

  • a unified formal language for the description and modelling of living, as well as artificial and cognitive systems, e.g. control theory, Bayesian inference, dynamical systems theory, etc.
  • the exploration of biological creatures enhanced by artificial systems (or artificial systems augmented with organic parts) in order to investigate the boundaries between living and nonliving organisms, and
  • the evaluation of coupled biological-artificial systems that could shed light on the importance of interactions among systems for the study of living and cognitive organisms.

This special sessions aims to invite contributions from the fields of psychology, computational neuroscience, HCI, theoretical biology, artificial intelligence, robotics and cognitive science to discuss current research on the formalisation, combination and interaction of artificial/living/cognitive systems from theoretical, modelling and implementational perspectives.

Potential topics include, but are not limited to:

  • Formalisation of life and cognition (e.g. dynamical systems theory, stochastic optimal control, Bayesian inference, etc.)
  • Cognitive robotics
  • Autopoiesis
  • Life-mind continuity thesis
  • Systems biology
  • Origins-of-life theories with relationships to artificial and cognitive systems
  • Animal-robot interaction
  • Bio-inspired robotics
  • Bio-integrated robotics
  • Human-machine interaction
  • Augmented cognition
  • Sensory substitution
  • Interactive evolutionary computation
  • Artificial perception

Machine Learning in ALife

Organiser: Nicholas Guttenberg

In recent years, machine learning has moved past the pure optimization perspective into exploring more complex interacting modes of learning and behavior. For example, techniques involving multiple competing agents have been used to produce photorealistic images, perform negotiations at a super-human level of performance, and to master the game of Go. These techniques have brought machine learning closer to the mainstay of ALife research and present opportunities for both fields to benefit from each others’ expertise and insight.

In this session, we would like to invite submissions which introduce new ideas from machine learning that may be interesting for ALife research, discuss ALife work which makes use of machine learning techniques, or which discuss or interpret phenomena from machine learning systems in light of an ALife perspective.

Topics of interest include (but are not limited to)

  • Using dynamical systems and complex systems theory to understand the dynamics of learning
  • Relationships between evolution, reinforcement learning, and supervised learning
  • ALife models using agents that learn
  • Multi-agent machine learning
  • Adversarial dynamics in machine learning (generative adversarial networks and the like)
  • Self-play and discovery
  • Communication between agents
  • Open-endedness and creativity in machine learning systems
  • Learned motivations / intrinsic motivations

Morphogenetic Engineering

Organisers: Rene Doursat, Hiroki Sayama
Web page:

This special session aims to promote and expand Morphogenetic Engineering, a field of research exploring the artificial design and implementation of autonomous systems capable of developing complex, heterogeneous morphologies. Particular emphasis is set on the programmability and controllability 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.

Traditional engineered products are generally made of a number of unique, heterogeneous components assembled in complicated but precise ways, and are intended to work deterministically following specifications given by their designers. By contrast, self-organization in natural complex systems (physical, biological, ecological, social) often emerges from the repetition of agents obeying identical rules under stochastic dynamics. These systems produce relatively regular patterns (spots, stripes, waves, trails, clusters, hubs, etc.) that can be characterized by a small number of statistical variables. They are random and/or shaped by boundary conditions, but do not exhibit an intrinsic architecture like engineered products do.

Salient exceptions, however, strikingly demonstrate the possibility of combining pure self-organization and elaborate architectures: biological development (the self-assembly of myriads of cells into the body plans and appendages of organisms) and insect constructions (the stigmergic collaboration of colonies of social insects toward large and complicated nests). These structures are composed of segments and parts arranged in very specific ways that resemble the products of human inventiveness. Yet, they entirely self-assemble in a decentralized fashion, under the control of genetic or behavioral rules stored in every agent.

How do these collectives (cells or insects) achieve such impressive morphogenetic tasks so reliably? Can we export their precise self-formation capabilities to engineered systems? What are principles and best practices for the design and engineering of such morphogenetic systems?

Topics of interest:

  • New principles of morphogenesis in artificial systems
  • Bio-inspiration from plant vs. animal development
  • Programmability of self-organizing morphogenetic systems
  • Indirect, decentralized control of morphogenetic systems
  • Sensitivity to environmental/boundary conditions vs. endogenous drive
  • Evolvability, by variations and selection, of morphogenetic systems
  • Links with evolutionary computation, artificial embryogeny, “evo-devo” approaches
  • Swarm-based approaches to morphogenetic systems
  • Design techniques for morphogenetic engineering
  • Causalities between micro and macro properties of morphogenetic systems
  • Physical implementations
  • Applications to real-world problems (swarm robots, synthetic biology, complex networks, etc.)
  • Philosophical questions about morphogenetic engineering