The International Conference on Guided Self-Organisation (GSO-2018): Information Geometry and Statistical Physics

The goal of Guided Self-Organization (GSO) is to leverage the strengths of self-organization (i.e., its simplicity, parallelization, adaptability, robustness, scalability) while still being able to direct the outcome of the self-organizing process. GSO typically has the following features:

(i) An increase in organization (i.e., structure and/or functionality) over time;

(ii) Local interactions that are not explicitly guided by any external agent;

(iii) Task-independent objectives that are combined with task-dependent constraints.

GSO-2018 is the 9th conference in a bi-annual series on GSO. Recent research is starting to indicate that information geometry, nonequilibrium statistical physics in general, and the thermodynamics of computation in particular, all play a key role in GSO. Accordingly, a particular focus of this conference will be the interplay of those three topics as revealed by their relationship with GSO.

The following specific topics are of special interest:

• information-driven self-organisation
• complex systems and networks
• non-equilibrium statistical physics
• non-extensive statistical mechanics
• physics of information and computation
• information dynamics
• generalised entropies
• generalised relative entropies
• alpha geometry and alpha statistics
• constraints and maximum entropy principle
• information-geometric aspects of Fokker-Planck and Kolmogorov equations