The following workshops will take place on September 4th as satellite events of ECAL 2017.
Morphogenetic Engineering Workshop
Monday 4 Sept 09:00 – 12:30 • Huma. Amphi EST
Organizers
Rene Doursat, Manchester Metropolitan University
Hiroki Sayama, Binghamton University
Description
This workshop aims to promote and expand Morphogenetic Engineering, a new 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?
Living architectures
Monday 4 Sept 09:00 – 17:30 • René Char
Organizers
Martin Hanczyc (University of Trento, Italy)
Andy Adamatzky (UWE, Bristol, UK)
Barbara Imhof (LIQUIFER Systems Group GmbH, Vienna, Austria)
Juan Nogales Enrique (Centro de Investigaciones Biologicas, Madrid, Spain)
Description
Living Architecture is about buildings that function and behave as living creature: they breathe, think, dream, and fall in love with their inhabitants. Living Architecture can be thought as a step “beyond” biomimicry where things are not “like” biological systems, they have original physiology and perform “as” living things, so that these spaces are new kinds of localised nature as it were that is programmable. Living Architecture looks at forms of programmable matter and programmable environments (where spatial relationships between things starts to create effects – contingencies and position in time and space actually influence events), where technological convergences are forming new kinds of organisms — organisms that we can inhabit and have a physical/chemical/computational conversation with. Topics included but not limited to are protocols for ‘synthetic ecosystem’ design and engineering foundational concepts for computationally processing, recycling, remediating and synthesising valuable compounds from waste; transferable principles for the construction of living architecture; evolutionary design of buildings and cities; neural networks integrated into buildings; self-growing buildings; architectural concepts borrowed from plants, social insects and aquatic environments; speculations on would-be cities of future and integration of human beings into fabric of building environment.
Agency In The Physical Sciences
Monday 4 Sept 09:00 – 17:30 • Huma. Amphi OUEST
Organizers
Eran Agmon, Columbia University, US
Martin Biehl, Araya, Japan
Christopher L Buckley, University of Sussex,UK
Simon McGregor, University of Sussex, UK
Nathaniel Virgo , Tokyo Institute of Technology, Japan
Olaf Witkowski, Tokyo Institute of Technology, Japan
Description
The study of agents in physical or physics-like systems is at the foundation of artificial life. The concept of an agent can be seen as an abstraction of living organisms that focuses more on action, perception, and goal-directedness (normativity if you like) than replication and growth. Many systems studied in artificial life research e.g. cellular automata and reaction-diffusion systems can be seen as artificial physics that exhibit primitive “agent-like” structures. “Agent-like” currently remains an intuitive classification; this workshop aims to provide a platform for research directed towards making such a classification in a formal or quantitative way.
More precisely, this workshop addresses questions like:
● What sorts of physical structures can be said to be agents?
● What can be gained by understanding them as agents?
● What sorts of agents are they?
● And by virtue of what physical properties are they those sorts of agents?
This workshop aims to explore questions relating to agency in its most primitive forms, both in simulation and in physical reality. To this end, we invite both theoretical and empirical contributions on primitive agency.
● The emphasis for theoretical contributions is on clear definitions and quantification: we are most interested in concepts that lend themselves to a rigorous analysis.
● Empirical contributions should describe apparently purposeful, or otherwise apparently agentive, behaviour in systems simpler than those previously known to display such behaviour.
Evolution of Physical Systems (EPS)
Monday 4 Sept 14:00 – 17:30 • Rotonde
Organizers
John Rieffel, Union College, US
Jean-Baptiste Mouret, INRIA, France
Nicolas Bredeche, UPMC, France
Evert Haasdijk, Vrije Universiteit Amsterdam, Netherlands
Description
We use the term Evolution of Physical Systems (EPS) to refer to evolutionary algorithms which occur entirely in real-world physical substrates rather than in simulation. The term encompasses both parallel Embodied Evolution (Watson et al., 2002), in which evolution is distributed across a population of robots, as well as Evolutionary Robotics (Floreano and Mondada, 1994) where evaluation is serialized on a single robot. Notable examples of EPS occur across a wide variety of systems, ranging from Robotics (Zykov et al., 2004)] to FPGAs (Thompson, 1996) to 3D printers (Rieffel and Sayles, 2010). Although EPS comes at a cost (the speed of the real world, unlike CPUs, does not follow Moore’s Law), by definition it avoids the “reality gap” imposed by simulation, and has produced novel and tangeable real-world results. Regardless of application or method, all implementations of EPS are bound by many of the same constraints and technical challenges.
This workshop is the concluding workshop in a series that began at ALIFE in 2012, and culminated in the forthcoming Special Issue of Artificial Life Journal devoted to the topic. This workshop will give authors of the special issue an opportunity to discuss their research. More broadly, we hope to continue our mission to bring together researchers who are currently involved in the Evolution of Physical Systems, as well as those interested in the technique, in order to share ideas and innovations. As the frontiers of artificial life move from the computer to the petri dish, the Evolution of Physical Systems offers to provide inroads into domains which are otherwise impossible to simulate.
The Second Workshop on Social Learning and Cultural Evolution (SLACE): What is social learning and where is it going?
Monday 4 Sept 14:00 – 17:30 • Huma. 111
Organizers
Julien Hubert, Vrije Universiteit Amsterdam
Jacqueline Heinerman, Vrije Universiteit Amsterdam
Evert Haasdijk, Vrije Universiteit Amsterdam
Chris Marriott, University of Washington, USA
James Borg, Keele University, UK
Peter Andras, Keele University
Description
The fields of social learning and cultural evolution aim at understanding how the exchange of knowledge within a group of individuals influences their performance. While cultural evolution focuses on how collective knowledge evolves over time within a population, social learning is concerned with the exchange of knowledge among individuals. Cultural evolution builds upon the mechanisms offered by social learning. This relationship is visible within the Alife community as social learning and cultural evolution are studied using similar methodologies, such as evolutionary robotics. This edition of the workshop will mainly, but not exclusively, focus on social learning.
With the rapid technological progress in robotics and artificial intelligence, intelligent robots will enter our society within a few years. These robots will need to adapt to an unpredictable environment while learning new tasks without supervision. This implies a capacity to learn autonomously and efficiently the diverse skills required by their task. Learning can be achieved through reinforcement learning or evolutionary robotics, but the time and trials required by these methods may be prohibitive. Social learning can contribute to solving this problem as it allows robots to request the necessary knowledge from others, reducing the temporal cost of learning.
Social learning research is still in its infancy. Currently, the main outcome of research in this field is the increase in learning speed it provides, but many open questions remain. For instance, for which tasks social learning is advantageous, what information should be transferred, how to merge conflicting information, how to rate and assess sources of information, etc. Such questions need to be answered so that social learning can optimally support the future robotic society. The theme of the workshop is to discuss the open questions and to identify promising future research directions in social learning.
What can Synthetic Biology offer to (Embodied) Artificial Intelligence (and vice versa)?
Monday 4 Sept 14:00 – 17:30 • Huma. Amphi EST
Organizers
Luisa Damiano, University of Messina, Italy
Yutetsu Kuruma, Tokyo Institute of Technology, Japan
Pasquale Stano, University of Salento, Italy
Description
Traditionally Artificial Intelligence (AI) research, broadly conceived as the study of intelligence through the construction of artificial models of natural cognitive systems, has been developed in the context of computer science and robotics. Today the emergence of Synthetic Biology (SB), conceived as the chemical synthesis of biological parts/systems/processes, allows the scientific community to extend AI research within the field of experimental biology.
The workshop aims at offering an interdisciplinary forum in which nascent programs involving cooperation between SB and AI in the exploration of biological and cognitive processes can be discussed in their groundings, their procedures, their possibilities and their limits, as well as enriched through scientific exchange of ideas.
The main focus will be double. On one side, we are interested on current and possible applications in AI research of the emerging SB front –line research, with a particular attention for bio-chemical based Information and Communication Technologies (ICT) founded on the convergence of biological, chemical, and physical approaches, often in combination with progresses in miniaturization like micro-fluidic devices and Micro Electro-Mechanical Systems (MEMS). On the other side, the workshop points to actual and possible approaches and research programs that involve AI in SB research.
Most of the participants will have a SB, AI, and/or bio- chem-ICT background, or come from scientific disciplines dealing with theoretical, epistemological and/or experimental issues related to the synthetic study of life and cognition. Our goal is to stimulate the interaction between applied and theoretical research, as well as epistemological reflection, and to support a front line in SB and AI focusing on (some of) these questions:
• Can intelligence be studied through the construction and exploration of synthetic biological systems and processes? In which conditions? More specifically: What can SB, and in particular its bio-chem-ICT tools and issues, offer to AI?
• Which are the groundings, procedures, possibilities, limits, expected results, and impacts of current and possible research programs involving SB in AI research? How AI will advance by encompassing SB and bio- chem-ICT approaches?
• Can we nowadays plan concrete collaborations between computer science, robotics and SB in the scientific study natural forms of intelligence? How?
• Are the emerging directions of research in AI (such as embodied AI, enactive AI, soft robotics, …) good candidate to cooperate with SB in the exploration of natural forms of cognition? Can SB contribute to the development of artificial forms of cognition (artificial cognitive systems which do not model natural cognitive systems)?
The workshop intends to bring together researchers interested in investigating one or more of these aspects of the (possible/actual) relationships between SB and AI. The aim is developing an interdisciplinary dialogue able to promote the reflected involvement of SB in AI, and to create a interdisciplinary community concretely developing research programs based on the cooperation of SB and AI.
Multidisciplinary Applications of Evolutionary Game Theory CANCELLED
Organizers
Tom Lenaerts , Université Libre de Bruxelles, Belgium
Luis A. Martinez-Vaquero, Institute of Cognitive Science and Technology, Italy
Jelena Grujic, Vrije Universiteit Brussel, Belgium
Francisco C. Santos, University of Lisbon, Portugal
Chaitanya Gokhale, Max-Planck Institute for Evolutionary Biology, Plön, Germany
Description
Evolutionary game theory (EGT) joins mathematical concepts of classical game theory with evolutionary principals from biology. The theory has been shown to be very fruitful in modeling 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.
EGT is profoundly interdisciplinary and the flow of knowledge between different fields is of crucial importance for its future development and application. The goal of the workshop is to show the state-of-the-art of the field and connect researchers with different backgrounds, from physicists and computer scientists to biologists, economists and sociologists and invite them to share ideas and learn from each other.
EGT provides a theory fundamental for the creation of agent-based models, a methodology that lies at the hart of Artificial Life research. The European Conference on Artificial Life in Lyon therefore offers an excellent event to encourage the interaction between researchers that use evolutionary theory provided by EGT to answer their scientific questions.
Through the connection of this workshop with ECAL and the Alife conferences, we also aim to attract researchers from other disciplines to discover the importance of these events for sharing their results and breakthroughs: many ideas from evolutionary game theory are finding applications in artificial life and many tools and algorithms from artificial life find their way back to evolutionary game theory.
Developmental learning and representation building in human-robots and ambient intelligence systems CANCELLED
Organizers
Amélie Cordier, Hoomano, France
Stephane Doncieux, ESIR-UPMC, France
Amal El Fallah Seghrouchni, LIP6, UPMC, France
Frank Guerin, University of Aberdeen, Scotland (UK)
Salima Hassas, LIRIS-CNRS University of Lyon 1, France (Primary Contact),
Bipin Indurkhya, AGH University, Poland
Leonardo Lana De Carvalho, FIH / UFVJM, Brazil
Mathieu Lefort, LIRIS-CNRS University of Lyon 1, France
Georgi Stojanov, American University of Paris, France
Description
The aim of the workshop is to bring together researchers interested in developmental learning and bio-inspired approaches for artificial cognitive systems and practitioners from digital industries, robotics and Ambient Intelligence systems, to exchange their knowledge and experiences regarding the question of building representations in human-robots and Ambient Intelligence Systems.
The workshop’s aim is also to cross fertilize the exchanges between participants from different disciplines and sectors, around the progress of the state of the art in foundational theories and their potential transfer and deployment in applications in real world settings, with robots and Ambient Intelligence Systems. A particular attention will be paid to steer the program towards bridging the gap between theory and practice.
This event will be backed by the project Behaviors.ai (Project of a joint laboratory between the LIRIS- CNRS laboratory and the Hoomano company). The aim of Behaviors.ai is to investigate new approaches of artificial intelligence, and more precisely developmental learning, to create new ways to interact with social robots to make them more empathetic and able to continuously learn as they interact in “real life” environments.
The focus of the workshop will be on the issue of autonomous “Representation building”, in artificial cognitive systems, through internal mechanisms, following bio-inspired approaches and developmental learning approaches, especially considering hybrid systems involving humans and artificial systems like robots or ambient intelligence systems. In this context, the following (non exhaustive) list of topics would be of interest:
– co-construction of meaning between human artificial agents (robots/ambient system)
– Abstracting representations from sensorimotor patterns to higher level cognitive capacities;
– Bio-Inspired mechanisms for cognitive self-development;
– Potential applications of developmental theories in robotics and ambient artificial intelligent systems
– Knowledge transfer, transfer learning, representation sharing ..
– Evolutionary approaches and mechanisms for cognitive development in artificial systems
Machine Learning as Open-Ended Evolution CANCELLED
