- ALife Conference
Tutorial - Functional programming for artificial life
Tutorial - Visualization Principles and Techniques for Research in ALife
About what life means and how it can be defined from the point of view of physics/information theory, etc.
Melanie Mitchell, keynote Lecture
This talk was very similar to another one I watched from Santa Fe Institute which promotes her book: Artificial Intelligence: A Guide for Thinking Humans.
It gives a detailed breakdown of why machine learning still fails at many tasks and might not be able to overcome them before we change the current way of doing it. The main takeaway for me is that Mitchell believes we will need to somehow build abstraction or conceptualization capabilities within our ML models to make them able to use “common sense” and understand things we consider as basic.
Contributed session 1
Djordje Grbic, Sebastian Risi - Safe Reinforcement Learning through Meta-learned Instincts
Toby Howison, Josie Hughes, Fumiya Iida - Morphologically programming the interactions of V-shaped falling papers
Interesting talk about falling V-shaped papers. The range of exhibited behavior is surprising and is an instance of complex systems with a few controllable parameters but surprising dynamics.
Cem Tutum, Risto Miikkulainen - Adapting to Unseen Environments through Explicit Representation of Context
Manon Flageat, Antoine Cully - Fast and stable MAP-Elites in noisy domains using deep grids
Julian F. Miller: Evolving developmental neural networks to solve multiple problems
This talk is about introducing a new model of neural network neuron that could have enough modularity to deal with multiple problems at once.
Peter Andras - Composition of Games as a Model for the Evolution of Social Institutions
Socials institutions can be seen as large games with rules, norms, and values. They are complex evolving systems starting form simple cooperation and evolving to complex things. The author applies a game theory framework to these systems.
James M. Borg, Matt Grove, Fiona Polack - Coloured noise time series as appropriate models for environmental variation in artificial evolutionary systems
Many biological time-series exhibit a type of colored noise. The authors use different noise functions in evolutionary models and observe that it profoundly affect the evolutionary response. This is interesting because it shows that the most often used white noise (Gaussian noise) might not be the best choice for evolution simulations.
Contributed session 2
Randall D. Beer - An Integrated Perspective on the Constitutive and Interactive Dimensions of Autonomy
Mark Bedau - Dynamic natural kinds: Open-ended evolution in the joints of nature
The authors use word2vec on patents to identify technological feature spaces. The similarity between patent descriptions is used to measure their proximity. This offers and interesting perspective on the space of different technologies and their hierarchical and dynamical properties.
Acacia Ackles, Austin Ferguson, Connor Grady, Charles Ofria - Rank epistasis: A new model for analyzing epistatic interactions in the absence of quantifiable fitness interactions
This paper studies an epistasis model. The new proposed model is based on ranking loci of a genetic model based on their fitness. Then, after mutating a locus and computing the new ranking. By comparing statistical differences between the two rankings one can estimate the effect of the previously introduced mutation.
The authors used NK model to study the new metric in a relatively well studied environment. Sites with higher epistatic activity score higher according to their metric and this happens without any a priori information about how the sites interact with each other.
Thomas Helmuth, Edward Pantridge, Grace Woolson Lee Spector - Genetic Environment Sensitivity and Transfer Learning in Genetic Programming
Mahi Luthra, Eduardo J. Izquierdo, Peter M. Todd - Cognition Evolves with the Emergence of Environmental Patchiness
Using a simple agent based simulation of animals and plants in a grid world, the authors observe spontaneous “patchiness” of the partition of plants. Cognition, defined as the ability perceptual strength of an agent and the stochasticity of its decisions increases and stabilizes in those simulations.
When cognition is not restricted, patches are larger and more visible, whereas for restricted cognition resource distribution is more uniform. There is a two way influence of both parameters on the evolution of patches and cognition.
Lauren Benso, Lauren Benson, Madhavun Candadai and Eduardo Izquierdo - Neural reuse in multifunctional circuits for control tasks
This talk is about studying a simple two-layers feedforward neural network evolved to solve three RL tasks at the same time. Then by introducing neuron lesions and their effect on the fitness, one is able to identify the useful neurons and their importance.
Many neurons are re-used across multiple tasks. With neural variance and mutual information within each neurons the authors are able to analyze the reuse of neurons.
The takeaways are :
- It seems relatively simple to obtain neuron reuse across tasks with simple evolutionary methods
- Successful neural networks on theses toy tasks appear to reuse their neurons
Contributed session 3
Shane St. Luce, Hiroki Sayama - Phase Spaces of the Strategy Evolution in the El Farol Bar Problem
Guillaume St-Onge, Antoine Allard, Laurent Hébert-Dufresne - Localization, bistability and optimal seeding of contagions on higher-order networks
In this talk, the author studies higher-order networks, which differently from simple networks, have interactions that can exist within groups of elements (instead of pairs). This allows studying contagion and spreading dynamics from a new angle.
Juan Perez-Mercader - Non-biochemical autonomous synthesis and boot-up from a chemical homogeneous mixture of a population of vesicles: their birth, growth, self-replication, extinction and competition cycles
Abe Leite, Madhavun Candadai and Eduardo J. Izquierdo - Reinforcement learning beyond the Bellman equation: Exploring critic objectives using evolution
Thomas Helmuth, Lee Spector - Explaining and Exploiting the Advantages of Down-sampled Lexicase Selection
Oskar Elek, Joseph N. Burchett, J. Xavier Prochaska and Angus G. Forbes - Monte Carlo Physarum Machine: Agent-based Model for Reconstructing Complex 3D Transport Networks
Cosmic web is diffuse, not only composed of galaxies but hot and cold gas and dark matter. It is very hard to capture from experimental data. Authors use the slime mold as a model for reconstructing this network. This mold is interesting because by using gradients of chemicals emitted by food and itself, it can construct near-optimal transport networks. Their model is also inspired from Sage Jensons’s cyber critters adapted to 3D. They use Monte-carlo sampling of directions around the gradient for moving each tiny agent which results in more natural-looking simulations.
This model reproduces the cosmic web in a relatively faithful way visually, and is robust thanks to its stochastic component.
Contributed session 4
Matthew Egbert - Marangoni Based Motile Oil-Droplets in Simulated Artificial Chemistry
Nicolas Lobato-Dauzier, Leo Cazenille , Teruo Fujii, Anthony Genot and Nathanael Aubert-Kato -Temperature-based inputs for molecular reservoir computers
Azumi Mamiya, Genki Ichinose - Zero-Determinant Strategies under Observation Errors
Ekaterina Sangati, Simon M. Hofmann - The Role of Co-Representations in Joint Tracking
Palin Choviwatana, Shota Ejima, Mizuki Oka, Takashi Ikegami - Web as an Evolutionary Ecosystem: Emergence of Keystone Species
Contributed session 5
Hoang Nguyen, Peter Banda, Darko Stefanovic, Christof Teuscher - Reservoir Computing with Random Chemical Systems
Zineb Elhamer, Reiji Suzuki, Takaya Arita - Hybrid Approach to Understanding Continuous Social Dynamics Based on A Large-Scale Modeling and A Face-to-Face Experiment
Hiroki Sato, Itsuki Doi, Yasuhiro Hashimoto, Mizuki Oka, Takashi Ikegami - Selection and Accelerated Divergence in Hashtag Evolution on a Social Network Service
Michael L Wong and Stuart Bartlett - Defining Lyfe in the Universe: From Three Privileged Functions to Four Pillars
Wen-Chi Yang, Yuh-Huey Lee, Kuo-Shih Yang - Modeling the Impact of Social Comparison on Student Engagement by the Equity Theory
Manh Hong Duong, The Anh Han - The effect of mutation on equilibrium properties of deterministic and random evolutionary games
Matthew Dale - Designing Computational Substrates using Open-Ended Evolution
This poster is about characterizing the computational capabilities of reservoir computing systems. The author’s goal is to design computational substrates that have interesting properties when used as reservoir computing basis.
For this, the authors have to define a behavior space that they slice up into voxels. They use novelty search to explore that space and measure the quality of the possible behavior.
Elissa Cohen - Resilient Life: An Exploration of Perturbed Autopoietic Patterns in Conway’s Game of Life
Contributed session 6
Contributed session 7
Contributed session 8
Contributed session 9
Contributed session 10
Demyan Vakhrameev, Xabier Barandiaran, Miguel Aguilera, Manuel Bedia - Measuring Autonomy for Life-Like AI
Léni K. Le Goff, Emma Hart, Agoston E. Eiben - Sample and time-efficient policy learning with CMA-ES and Bayesian Optimisation
Paul Ecoffet, Jean-Baptiste André, Nicolas Bredeche - Learning to Cooperate in a Socially Optimal Way in Swarm Robotics
Payam Zahadat, Ada Diaconescu - Reactive or Stable: A Plant-inspired Approach for Organisation Morphogenesis
Edmund Hunt, Nigel R. Franks, Roland J. Baddeley - The Bayesian Superorganism: Collective Probability Estimation in Swarm Systems
Tim Taylor - The Importance of Open-Endedness (for the Sake of Open-Endedness)
Asheesh Sharma, Sabine Hauert and Helmut Hauser - Morphological communication for swarms
Contributed session 11
Gunnar Tufte, Johannes H. Jensen - Reservoir Computing in Artificial Spin Ice
Stephan Scheidegger, Alexander Mikos, Harold Fellermann - Modelling Artificial Immune – Tumor Ecosystem Interaction During Radiation Therapy Using a Perceptron – Based Antigen Pattern Recognition
Juste Raimbault - A model of urban evolution based on innovation diffusion
Merihan Alhafnawi, Sabine Hauert, Paul O’Dowd - Robotic Canvas: Interactive Painting onto Robot Swarms
Léni K. Le Goff, Emma Hart, Stéphane Doncieux, Alexandre Coninx - On Pros and Cons of Evolving Topologies with Novelty Search
Novelty search is used in simple maze and navigation tasks and different evolved and non evolved architecture are compared.
Ditlev Hartmann Bornebusch, Christina C. Soerensen, Peter Zingg, Gianluca Gazzola, Norman Packard and Steen Rasmussen
Rebecca Kramer-Bottiglio keynote Lecture
This keynote was about using robotic skins to make soft and “natural”-looking robots. This allows to transform inert object into actuators or moving robots.
Kramer’s team is developing molecules and composite materials with multiple functionalities.
- Talk: Alife 2020 keynote Lee Cronin - A Top Down Chemically Embodied Artificial Life Computation
- ALife Conference
- Notes on: Adapting to Unseen Environments through Explicit Representation of Context by Tutum, C., & Miikkulainen, R. (2020)
- Notes on: Fast and stable MAP-Elites in noisy domains using deep grids by Flageat, M., & Cully, A. (2020)
- Notes on: Resilient Life: An Exploration of Perturbed Autopoietic Patterns in Conway’s Game of Life by Cika, A., Cohen, E., Kruszewski, G., Seet, L., Steinmann, P., & Yin, W. (2020)
- Notes on: Safe Reinforcement Learning through Meta-learned Instincts by Grbic, D., & Risi, S. (2020)
- Notes on: A model of urban evolution based on innovation diffusion by Raimbault, J. (2020)
- Talk: Alife 2020 keynote Michael Levin - Robot Cancer
- Talk: Alife 2020 keynote Luis Zaman - New Frontiers in Alife: What was old is new again