Algorithmic Foundations of Emergent Behavior in Analog Collectives

Explore the algorithmic foundations of emergent behavior in analog collectives through this comprehensive lecture. Delve into self-organizing systems, programmable matter, and the challenges of top-down versus bottom-up approaches. Examine the differences between digital and analog systems, and investigate key concepts such as aggregation, compression, and connectivity. Learn about BobBots, color systems, and separation techniques. Understand the Metropolis-Hastings algorithm, stationary distribution, and one-line proofs. Analyze simulations, phase changes, and various examples to grasp the intricacies of the model. Gain insights into the complex world of emergent behavior and its applications in analog collectives.

Introduction
Selforganizing systems
Top down and bottom up
Programmable Matter
Challenges
Algorithms and Behavior
Digital vs Analog
Aggregation
Compression
BobBots
Connectivity
Color Systems
Separation
Metropolis Hastings
Stationary Distribution
OneLine Proof
Simulation
Phase Change
Wrapping Up
Examples
The Model
Conclusion
Comment