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Self-Organized Construction by Minimal Surprise
Here, we apply minimal surprise to collective construction.
Innate Motivation for Robot Swarms by Minimizing Surprise: From Simple Simulations to Real-World Experiments
Applications of large-scale mobile multi-robot systems can be beneficial over monolithic robots because of higher potential for robustness and scalability.
Learning from Evolution: Improving Collective Decision-Making Mechanisms using Insights from Evolutionary Robotics
Collective decision-making enables multi-robot systems to act autonomously in real-world environments.
Evolution of Collective Decision-Making Mechanisms for Collective Perception
Autonomous robot swarms must be able to make fast and accurate collective decisions, but speed and accuracy are known to be conflicting goals.
Engineered Self-Organization for Resilient Robot Self-Assembly with Minimal Surprise
There is no task-dependent bias or any other explicit predetermination for the different qualities of the emerging patterns.
