Complex Systems and Dynamics

Flow-Lenia: Emergent evolutionary dynamics in mass conservative continuous cellular automata

Central to the artificial life endeavour is the creation of artificial systems spontaneously generating properties found in the living world such as autopoiesis, self-replication, evolution and...

Revealing hidden correlations from complex spatial distributions: Adjacent Correlation Analysis

Physics has been transforming our view of nature for centuries. While combining physical knowledge with computational approaches has enabled detailed modeling of physical systems' evolution,...

Information Flow Rate for Cross-Correlated Stochastic Processes

Causal inference seeks to identify cause-and-effect interactions in coupled systems. A recently proposed method by Liang detects causal relations by quantifying the direction and magnitude of...

When Your Own Output Becomes Your Training Data: Noise-to-Meaning Loops and a Formal RSI Trigger

We present Noise-to-Meaning Recursive Self-Improvement (N2M-RSI), a minimal formal model showing that once an AI agent feeds its own outputs back as inputs and crosses an explicit...

Self-Organizing Graph Reasoning Evolves into a Critical State for Continuous Discovery Through Structural-Semantic Dynamics

We report fundamental insights into how agentic graph reasoning systems spontaneously evolve toward a critical state that sustains continuous semantic discovery. By rigorously analyzing structural...

Autocurricula and the Emergence of Innovation from Social Interaction: A Manifesto for Multi-Agent Intelligence Research

Evolution has produced a multi-scale mosaic of interacting adaptive units. Innovations arise when perturbations push parts of the system away from stable equilibria into new regimes where...

Probabilistic Behavioral Distance and Tuning - Reducing and aggregating complex systems

Given a complex system with a given interface to the rest of the world, what does it mean for a the system to behave close to a simpler specification describing the behavior at the interface? We...

Information Decomposition based on Cooperative Game Theory

We offer a new approach to the information decomposition problem in information theory: given a 'target' random variable co-distributed with multiple 'source' variables, how can we decompose the...

Multiscale Governance

Future societal systems will be characterized by heterogeneous human behaviors and also collective action. The interaction between local systems and global systems will be complex. Humandemics...

Classification of Discrete Dynamical Systems Based on Transients

In order to develop systems capable of artificial evolution, we need to identify which systems can produce complex behavior. We present a novel classification method applicable to any class of...

Evolutionary Innovations and Where to Find Them: Routes to Open-Ended Evolution in Natural and Artificial Systems

This paper presents a high-level conceptual framework to help orient the discussion and implementation of open-endedness in evolutionary systems. Drawing upon earlier work by Banzhaf et al., three...

On Artificial Life and Emergent Computation in Physical Substrates

In living systems, we often see the emergence of the ingredients necessary for computation -- the capacity for information transmission, storage, and modification -- begging the question of how we...

A superstatistical formulation of complexity measures

It is discussed how the superstatistical formulation of effective Boltzmann factors can be related to the concept of Kolmogorov complexity, generating an infinite set of complexity measures (CMs)...

Unique Information via Dependency Constraints

The partial information decomposition (PID) is perhaps the leading proposal for resolving information shared between a set of sources and a target into redundant, synergistic, and unique...

Informative and misinformative interactions in a school of fish

It is generally accepted that, when moving in groups, animals process information to coordinate their motion. Recent studies have begun to apply rigorous methods based on Information Theory to...

Grounding Occam's Razor in a Formal Theory of Simplicity

A formal theory of simplicity is introduced, in the context of a "combinational" computation model that views computation as comprising the iterated transformational and compositional activity of...

Deep learning reveals hidden interactions in complex systems

Rich phenomena from complex systems have long intrigued researchers, and yet modeling system micro-dynamics and inferring the forms of interaction remain challenging for conventional data-driven...

Modes of Information Flow

Information flow between components of a system takes many forms and is key to understanding the organization and functioning of large-scale, complex systems. We demonstrate three modalities of...