7 citations · 16 across the 15 of their papers we have counts for
9 papers · 1 filter
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…