Emergent Organization

Emergent organization studies how complex, structured patterns arise spontaneously from simpler interactions within a system, far from equilibrium. Current research focuses on developing mathematical frameworks and computational methods, such as reinforcement learning and physics-informed machine learning, to understand and predict this self-organization across diverse scales, from microscopic particle systems to large-scale climate phenomena. These advancements are improving our ability to model and analyze complex systems, with applications ranging from optimizing multi-agent control to identifying and predicting extreme weather events. The ultimate goal is to establish fundamental principles governing emergent organization, bridging the gap between microscopic interactions and macroscopic behavior.

Papers

November 23, 2023

On Principles of Emergent Organization
Adam T. Rupe, James P. Crutchfield
Path Breaking Emergence General Principle Self Organization Statistical Mechanic Emergent Organization

July 3, 2023

Environmental effects on emergent strategy in micro-scale multi-agent reinforcement learning
Samuel Tovey, David Zimmer, Christoph Lohrmann, Tobias Merkt, Simon Koppenhoefer, Veit-Lorenz Heuthe, Clemens Bechinger, Christian Holm
Reinforcement Learning Multi Agent Reinforcement Learning Langevin Dynamic Environmental Change Critical Agent Emergent Organization

April 25, 2023

Unsupervised Discovery of Extreme Weather Events Using Universal Representations of Emergent Organization
Adam Rupe, Karthik Kashinath, Nalini Kumar, James P. Crutchfield
Extreme Event Self Organization Unsupervised Discovery Universal Representation Coherent Structure Emergent Organization

July 3, 2022

Government Intervention in Catastrophe Insurance Markets: A Reinforcement Learning Approach
Menna Hassan, Nourhan Sakr, Arthur Charpentier
Reinforcement Learning Multi Armed Bandit Policy Evaluation Reinforcement Learning Approach Intervention Policy Emergent Organization

May 26, 2022

Emergent organization of receptive fields in networks of excitatory and inhibitory neurons
Leon Lufkin, Ashish Puri, Ganlin Song, Xinyi Zhong, John Lafferty
Network Programming Receptive Field Inhibitory Neuron Emergent Organization

Emergent Organization

Papers

On Principles of Emergent Organization

Environmental effects on emergent strategy in micro-scale multi-agent reinforcement learning

Unsupervised Discovery of Extreme Weather Events Using Universal Representations of Emergent Organization

Government Intervention in Catastrophe Insurance Markets: A Reinforcement Learning Approach

Emergent organization of receptive fields in networks of excitatory and inhibitory neurons