7 citations · 16 across the 15 of their papers we have counts for
18 papers
On Growth and Form, and Function: Reusable Regulatory Handles Control Phenotypic Variation
Benedikt Hartl, Milton L. Montero, Marcello Barylli +2
How phenotypic transformations are implemented by changes in underlying regulatory dynamics remains a central question in developmental biology. Inspired by D'Arcy Thompson's 1917…
The Artificial Experimentalist: Discovery and Control of Self-Organizing Phenomena with Autotelic Reinforcement Learning
Marko Cvjetko, Benedikt Hartl, Michael Levin +2
Existing methods for exploring cellular automata and other complex systems mostly operate in open loop: they set initial conditions, execute a full simulation, and observe the outc…
Causal Organization Prior to and Promoting Self-Replication in a Catalytic Model of the Origin of Life
Federico Pigozzi, Michael Levin
Agents that exert causal power in the world are thought to be the product of selection among diverse replicators. Whether organized causal structure can arise before replication an…
Limbomorphs
Alex Alvarez, Michael Levin
Artificial life systems are typically defined by a set of dynamical rules over an environment, an agent, or both, from which lifelike patterns may emerge. Gifbreeder is an animated…
Agnosiophobia in a virtual agent: behavioral and dynamical architecture in Lenia
Jesse Cool, Benedikt Hartl, Michael Levin +1
All embodied agents are fundamentally patterns in physiological or other excitable media, blurring the distinction between objects and processes. Emergent patterns with complex beh…
Training Ecosystems: A Computational Approach to Uncovering Learning Behavior in Unconventional Contexts
Adrita Samanta, Hananel Hazan, Michael Levin
Recent progress in diverse intelligence has shown simple learning capacities below the organism level - single cells and even molecular networks. However, there are still many know…
The Causally Emergent Alignment Hypothesis: Causal Emergence Aligns with and Predicts Final Reward in Reinforcement Learning Agents
Federico Pigozzi, Michael Levin
A hallmark of life on Earth is the ability of agents to exert causal power and be drivers of subsequent events. This is key to cognition at all scales. Causal emergence, measuring…
A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need
Hananel Hazan, Yanbo Zhang, Benedikt Hartl +1
How many of a neural network's parameters actually encode task-specific information? We investigate this question with LottaLoRA, a training paradigm in which every backbone weight…
BraiNCA: brain-inspired neural cellular automata and applications to morphogenesis and motor control
Léo Pio-Lopez, Benedikt Hartl, Michael Levin
Most of the Neural Cellular Automata (NCAs) defined in the literature have a common theme: they are based on regular grids with a Moore neighborhood (one-hop neighbour). They do no…
Equilibrium flow: From Snapshots to Dynamics
Yanbo Zhang, Michael Levin
Scientific data, from cellular snapshots in biology to celestial distributions in cosmology, often consists of static patterns from underlying dynamical systems. These snapshots, w…
Neural cellular automata: applications to biology and beyond classical AI
Benedikt Hartl, Michael Levin, Léo Pio-Lopez
Neural Cellular Automata (NCA) represent a powerful framework for modeling biological self-organization, extending classical rule-based systems with trainable, differentiable (or e…
Open Questions about Time and Self-reference in Living Systems
Samson Abramsky, Wolfgang Banzhaf, Leo S. D. Caves +5
Living systems exhibit a range of fundamental characteristics: they are active, self-referential, self-modifying systems. This paper explores how these characteristics create chall…
What Lives? A meta-analysis of diverse opinions on the definition of life
Reed Bender, Karina Kofman, Blaise Agüera y Arcas +1
The question of "what is life?" has challenged scientists and philosophers for centuries, producing an array of definitions that reflect both the mystery of its emergence and the d…
Topological constraints on self-organisation in locally interacting systems
Francesco Sacco, Dalton A R Sakthivadivel, Michael Levin
All intelligence is collective intelligence, in the sense that it is made of parts which must align with respect to system-level goals. Understanding the dynamics which facilitate…
Bio-inspired AI: Integrating Biological Complexity into Artificial Intelligence
Nima Dehghani, Michael Levin
The pursuit of creating artificial intelligence (AI) mirrors our longstanding fascination with understanding our own intelligence. From the myths of Talos to Aristotelian logic and…
Heuristically Adaptive Diffusion-Model Evolutionary Strategy
Benedikt Hartl, Yanbo Zhang, Hananel Hazan +1
Diffusion Models represent a significant advancement in generative modeling, employing a dual-phase process that first degrades domain-specific information via Gaussian noise and r…
Diffusion Models are Evolutionary Algorithms
Yanbo Zhang, Benedikt Hartl, Hananel Hazan +1
In a convergence of machine learning and biology, we reveal that diffusion models are evolutionary algorithms. By considering evolution as a denoising process and reversed evolutio…
Neuroevolution of Decentralized Decision-Making in N-Bead Swimmers Leads to Scalable and Robust Collective Locomotion
Benedikt Hartl, Michael Levin, Andreas Zöttl
Many microorganisms swim by performing larger non-reciprocal shape deformations that are initiated locally by molecular motors. However, it remains unclear how decentralized shape…