Stacks Image 114305


Dates - July 13-18, 2020
Location - Virtual
Organizers - Vermont Complex Systems Center, University of Vermont
Hashtag - #ALIFE2020

Many of the Satellite Sessions listed below have open calls for contribution, please check out their websites for more information about call deadlines.

    ALife for Social and Environmental Good (ALife4Good)

    Stacks Image 113499
    Alife Slack Channel: #workshop-ALife4Good

    Keywords: artificial life, social good, sustainability, biosphere preservation, AI for good, positive future impact

    Organizers: Olaf Witkowski (Cross Labs, Tokyo, Japan), Alan Dorin (Monash University, Melbourne, Australia), Julien Hubert (Progress Technologies, Tokyo, Japan), Jitka Cejkova (University of Chemistry and Technology, Prague, Czech Republic), Steen Rasmussen (University of Southern Denmark & Santa Fe Institute, NM, USA), Manuel Baltieri (Riken, Tokyo, Japan), Antoine Pasquali (Cross Labs, Tokyo, Japan)

    Call For Contributions: Currently Open, see website below for more details
    Workshop overview: The purpose of this workshop is to discuss how Artificial Life research can benefit both human society and enhance the life of all organisms on the planet. The session will invite all participants to discuss the initiation of new means to encourage Artificial Life research towards sustained, positive impact with the potential to be felt beyond the field. This will be addressed via an open-ended discussion that begins to set objectives for consideration as end-goals, and for describing means by which progress towards the goals can be monitored or assessed.

    Twitter Handle: @ALife4Good

    Developmental Neural Networks Workshop (DevoNN)

    Stacks Image 113839
    Alife Slack Channel: #workshop-DevoNN

    Keywords: Development, Neural Networks, Artificial Intelligence, Neuroscience, Developmental Biology, Neurogenesis, Neuronal process, Synaptogenesis, Synaptic pruning

    Organizers: Julian F. Miller, Sylvain Cussat-Blanc, Dennis G. Wilson

    Call For Contributions: Currently Open, see website below for more details
    Workshop Description: In nature, brains are built through a process of biological development where structural aspects of the network change while learning. Incorporating development into ANNs raises fundamental questions, such as the balance between structural learning and synaptic learning. In this workshop, we will focus on the questions of neural development, an area that is under-explored in contemporary ANN literature.

    Emerging Researchers in Artificial Life

    Stacks Image 114331
    Alife Slack Channel: #workshop-eral

    Organizers: Daniel Junghans, Austin J. Ferguson, Acacia Ackles, Alexander Lalejini

    Call For Contributions: Currently Open, see website below for more details
    The Emerging Researchers in Artificial Life (ERA) is the official student, post-doc, and junior researcher group for the International Society for Artificial Life (ISAL). The purpose of the ISAL student group is to provide opportunities for students and post-docs interested in artificial life to interact with each other, develop professionally, and contribute to the broader artificial life community. The goal of this workshop is to provide a venue for junior researchers to meet, share their work, and network.

    To give junior ALife researchers a minimal-barrier-to-entry venue to share their research with peers, we will offer sign-ups to give lightning talks on research at any stage of development, ranging from rough ideas for future projects to already published work. The workshop will conclude with ALife-themed academic karaoke, an entertaining social activity where participants present an unknown (to the presenter) series of ALife-themed slides.

    Lifelike Computing Systems Workshop (LIFELIKE)

    Stacks Image 113854
    Alife Slack Channel: #workshop-LIFELIKE

    Keywords: self-x properties, self-organization, self-explainability, self-improvement, self-awareness, autonomous learning, resilience, flexibility, organic computing

    Organizers: Anthony Stein, Sven Tomforde, Jean Botev, Peter Lewis

    Call For Contributions: Currently Open, see website below for more details
    The LIFELIKE Computing Systems Workshop is intended to provide a forum for discussing new insights and implications from adopting Artificial Life principles to technical computing systems deployed to flexibly and robustly act in real-world environments. Thereby, we explicitly emphasize the aspects of interpretability and explainability of the involved algorithms in order to provide a basis for system transparency already at the core of its mechanisms. Besides this self-explanatory property, further key ingredients to reach a specific level of intelligence are self-awareness and the resulting ongoing pursuit for continual self-improvement by means of learning and optimization. The resulting particular tension between increasing system viability through adopting life-like characteristics, while at the same time ensuring an appropriate degree of system explainability, validation and compliance to exploration boundaries, constitutes the main motivation and unique topic of LIFELIKE.

    Twitter: @lifelikecs

    Symbiosis in Artificial Life (SAL)

    Alife Slack Channel: #workshop-SAL

    Keywords: symbiosis, artificial life, mutualism, parasitism, evolution, commensalism

    Organizers: Anya E. Vostinar, Erik Hom, Luis Zaman

    Call For Contributions: Currently Open, see website below for more details
    Symbiosis, a close and long-term interaction between two or more organisms from different species, is a ubiquitous phenomenon, found at all levels of life and nearly every context that we have looked for it. This workshop aims to connect researchers interested in understanding symbiosis through artificial life by presenting the currently available models and discussing challenges, potential solutions, and next steps for the field.

    Twitter: @SALWorkshop

    Teaching with Artificial Life (TAL)

    Alife Slack Channel: #workshop-TAL

    Keywords: education, artificial life, evolution education, computer science education, object-oriented programming, experiential learning

    Organizers: Anya E. Vostinar, Barbara Z. Johnson, Michael Wiser

    Call For Contributions: Currently Open, see website below for more details
    Because Artificial Life spans the fields of computer science and biology, it offers a unique perspective on the education of novices in both of those fields. This workshop aims to bring together educators and researchers in artificial life to discuss the many ways in which artificial life can be used to teach both biology and computer science.

    Twitter: @TALWorkshop

    The First Proteus Workshop

    Stacks Image 113957
    Alife Slack Channel: #workshop-proteus

    Keywords: evolutionary algorithms, bio-inspired artificial intelligence, crowdsourcing, robotics, wet ALife

    Organizers: Josh Bongard, Nick Cheney, Melanie Moses
    Typically, investigators write code or build robots from scratch whenever starting a new AI or robotics project. This leads to specialized systems brittle to novel challenges, and lack of reproducibility. Or, off-the-shelf software such as TensorFlow is employed, which restricts work to well-studied phenomena such as synaptic plasticity. These efforts traditionally have difficulty integrating tightly with efforts in biology.

    To prove this cycle can be broken, we plan to develop and deploy an open-source, continually running, cloud-based code base in which increasingly protean machines (robots and computer-designed organisms) and protean algorithms (meta learners, architecture-altering methods) are automatically designed using biological change phenomena (BCPs) incorporated as software patches. We hope that such a system could help facilitate biology-to-ALife transdisciplinary work, and help to scale up our community’s collective efforts in this regard.

    To test how this approach accelerates transferal of adaptive mechanisms from biology to AI and robotics, we will host a series of workshops to initially brainstorm and then construct such a code base. Anyone willing and able to contribute code to such an effort is welcome to participate.

    Twitter: @DoctorJosh

    The Second International Workshop on Agent-Based Modelling for Human Behaviour (ABMHuB)

    Stacks Image 113975
    Alife Slack Channel: #workshop-ABMHuB

    Keywords: Agent-based modelling Behavioural science Communication Economy Logistics Learning Social networks Collective intelligence Emergent behaviour

    Organizers: Katarzyna (Kasia) Kozdon, Soo Ling Lim, Peter J. Bentley

    Call For Contributions: Currently Open, see website below for more details
    International Workshop on Agent-Based Modelling of Human behaviour brings together modelling and behavioural science to address questions related but not restricted to communication, teamwork, learning and emergent behaviours in fields such as economy, logistics and sociology.

    Twitter: #ALifeBehavior2020

    Interdisciplinary Approaches to A-Life and the Digital Arts (A-Life and the Arts)

    Alife Slack Channel: #workshop-ALifeandtheArts

    Keywords: interaction; machinic; dynamic media; machine learning; interaction; evolution; temporal shape

    Organizers: Chris Salter, Takashi Ikegami, Alexandre Saunier, Sofian Audry
    This hands on workshop explores the use of A-Life techniques in an area of growing research and creation practice: the new conception and design of complex interactive machines/ media environments for the arts as well as entertainment contexts.

    Twitter hashtag: #alifearts

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

    Alife Slack Channel: #special-HybridLifeIII

    Keywords: Dynamical systems theory, Stochastic optimal control, Cognitive robotics, Life-mind continuity thesis, Systems biology, Animal-robot interaction, Bio-inspired robotics, Bio-integrated robotics, Human-machine interaction, Augmented cognition

    Organizers: Manuel Baltieri, Keisuke Suzuki, Hiroyuki Iizuka, Olaf Witkowski, Lana Sinapayen
    Hybrid life III focuses on the use of unifying mathematical frameworks, composite (artificial+biological) architectures and coupled systems for cognition to address highly cross-disciplinary topics at the intersection of cognitive science, artificial systems and biology.

    ALIFE and Society

    Alife Slack Channel: #special-ALIFEandSociety

    Keywords: ALIFE/AI and societal challenges; Socio-Ecological-technical systems; steering complex systems; philosophy; ethics; politics; social sciences; ALIFE for the Anthropocene; synthetic biology/ecology; hybrid, living & lifelike complex systems; Co-evolution of self, society, biosphere/technology;

    Organizers: Alex Penn, JM Siqueiros
    A forum to discuss grand challenges within human socio-ecological-technical systems: ALIFE/AI for society; Philosophical, ethical & social issues; designing/steering hybrid, living and lifelike CAS; ALIFE for the Anthropocene; future visions

    Functional Programming for Artificial Life (FPAL)

    Stacks Image 114028
    Alife Slack Channel: #tutorial-FPAL

    Keywords: functional programming, lambda calculus, Haskell, monad, combinator, artificial chemistry, artificial cell

    Organizers: Lance R. Williams
    An introduction to the Haskell programming language will be followed by an in depth look at a combinator-based artificial chemistry implemented as an embedded language inside Haskell, and the demonstration of a series of increasingly complex artificial organisms built using this chemistry. The unique features of Haskell that make this possible will be emphasized throughout.

    Twitter Hashtag: #FPAL

    The Bibites : Getting the online community involved into Alife through game development (Bibites)

    Stacks Image 114380
    Alife Slack Channel: #special-Bibites

    Keywords: YouTube, simulation, continuous project

    Organizers: Léo Causssan
    The Bibites is an artificial ecosystem simulation using evolutionary algorithms to evolve both physical and behavioral components of the agents, implemented through biological reproduction.

    As Alife projects tend to be one-shots, released at once and then left aside, it's interesting to ask What can be gained from continuing a project and building a community around it ?

    Twitter: @TBibites

    Introduction to Artificial Gene Regulatory Networks (AGRN)

    Stacks Image 114347
    Alife Slack Channel: #tutorial-AGRN

    Keywords: Artificial gene regulatory network Gene expression Developmental processes Models Applications in Artificial Life

    Organizers: Sylvain Cussat-Blanc; Wolfgang Banzhaf
    This tutorial will introduce the biology of gene regulatory networks, from the genetic aspect to the dynamics of gene regulation. We will show how bio-inspired models can lead to intelligent algorithms by showing various applications of artificial gene regulatory networks in Artificial Life.

    Large Scale Agent Based Modelling with FLAME GPU 2 (FLAME GPU 2)

    Stacks Image 114072
    Alife Slack Channel: #tutorial-FLAMEGPU2

    Keywords: Agent Based Modelling and Simulation, GPUs, large scale simulation

    Organizers: Paul Richmond
    Modelling and simulation of complex problems has become an established ‘third pillar’ of science, complementary to theory and experimentation. The multi-agent approach to modelling allows complex systems to be constructed in such a way as to add complexity from understanding at an individual level (i.e. a bottom-up approach). This approach is extremely powerful in a wide range of domains as diverse as computational biology to economics and physics. Whilst multi-agent modelling provides a natural and intuitive method to model systems the computational cost of performing large simulations is much greater than for top-down, system level alternatives. In order for multi-agent modelling and simulation to be used as a tool for delivering excellent science, it is vital that simulation performance can scale by targeting readily available computational resources effectively. In other words, increasing the size of the model or its accuracy directly impacts the amount of computational time required to perform the simulation. The use of parallel resources allows us to reduce time constraints and thus scale up the size and increase the accuracy of the model . FLAME GPU 2 provides this computational capacity by targeting readily available Graphics Processing Units capable of simulating many millions of interacting agents with performance which exceeds that of traditional CPU based simulators. FLAME GPU 2 is the next generation of the FLAME GPU software, developed in the UK since 2008 and delivered as a tutorial at ALIFE in 2018 and 2019. FLAME GPU 2 is an agent-based modelling simulation platform that enables modellers from various disciplines like economics, biology and social sciences to easily write agent-based models. Importantly, it abstracts the complexities of the GPU architecture away from modellers to ensure that modellers can concentrate on writing models without the need to acquire specialist knowledge typically required to utilise GPU architectures. This tutorial is aimed at the intermediate level. No knowledge of GPUs is required however basic knowledge multi agent modelling approaches is expected (i.e. formulating a problem as a set of individuals within a system) as well as a basic programming ability. The tutorial format is an introductory lecture followed by participants being provided the opportunity to complete a hands on exercise using the FLAME GPU software. Participants will be provided dedicated GPU cloud resources for interactively configuring and running a large scale agent based model within FLAME GPU. By the end of the practical session, it is expected that the participants will understand how to write and execute a multi-agent model for FLAME GPU from scratch. Participants will leave with an appreciation of the key techniques, concepts, and algorithms which have been used.

    Molecular programming of swarms for ALife (MolProg)

    Alife Slack Channel: #tutorial-MolProg

    Keywords: Molecular programming Swarming Molecular robots Evolutionary optimization Reality gap In-vitro implementation

    Organizers: Nathanael Aubert-Kato, Leo Cazenille, Nicolas Lobato-Dauzier
    This tutorial will introduce molecular programming tools to implement a variety of in-vitro systems, ranging from arbitrary chemical reaction networks to swarms with more than a million individual units.

    Programming soft alife with SPLAT and ulam (HackSPLAT)

    Stacks Image 114118
    Alife Slack Channel: #tutorial-HackSPLAT

    Keywords: Soft alife, programming, robust-first computing, best-effort architecture, indefinite scalability, Movable Feast Machine, living computation, SPLAT, ulam

    Organizers: Dave Ackley
    Deterministic CPU/RAM computing is becoming unscalable and unsecurable. The Movable Feast Machine is an indefinitely scalable architecture based on best-effort correctness and robust, life-like software. This tutorial introduces the two main programming languages for the MFM.

    Tracing epidemics with agent-based and network based models (EpiAgeNet)

    Alife Slack Channel: #tutorial-EpiAgeNet

    Keywords: computational epidemiology, agent-based modeling, complex networks, pandemics, epidemics, ACEMod, spatiotemporal spread, molecular genotyping, evolution, small-world

    Organizers: Mikhail Prokopenko
    We will consider pros and cons of agent-based and network-based models for studying epidemics, tracing a spatiotemporal spread of epidemics across a nation. We will also explore how high-resolution molecular genotyping data can help to infer weighted genetic networks, tracing emergence and evolution of dominant strains.

    Visualization Principles and Techniques for Research in ALife (ALifeVis2020)

    Stacks Image 114145
    Alife Slack Channel: #tutorial-ALifeVis2020

    Keywords: information visualization, multidimensional data, network data, time-varying data

    Organizers: Michael McGuffin
    A tutorial on basic principles for designing charts and visualizations; example strategies for visualizing multidimensional data, network data, time-varying data; brief critique of example visualizations drawn from ALife literature.

    Twitter Handle: @MJMcGuffin

    Introduction to MABE, A tool for studying evolving systems and digital brains (MABE)

    Alife Slack Channel: #tutorial-MABE

    Keywords: Research Tool, Evolution, Neuro Evolution, Simulation

    Organizers: Clifford Bohm
    MABE is a modular agent-based digital evolution research tool that can quickly get you from hypothesis to results. In this tutorial, you can learn the basics of MABE and how you can start to use it.

    Cartesian Genetic Programming (CGP)

    Alife Slack Channel: #tutorial-CGP

    Keywords: Genetic programming, evolutionary algorithms, graphs, circuits, image processing, neural networks, artificial development

    Organizers: Julian Miller
    Cartesian Genetic Programming uses evolutionary algorithms to create graphs. These can represent many things (e.g. circuits, equations, neural networks). It can be a useful tool for creating the programs running inside artificial cells and neurons. It is widely applicable to many computational problems. It is easy to program.

    Virtual Creatures Competition

    Deadline for submissions: June 26, 2020

    Alife Slack Channel: #robots

    Keywords: robotics

    Organizers: Sam Kriegman

    Open AI Gym Hackathon

    Alife Slack Channel: #hackathon

    Keywords: Open AI Gym

    Organizers: Jack Felag