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Investigation of A Collective Decision Making System of Different Neighbourhood-Size Based on Hyper-Geometric Distribution
The study of collective decision making system has become the central part of the Swarm- Intelligence Related research in recent years.
Sooner than Expected: Hitting the Wall of Complexity in Evolution
We propose here the 'Wankelmut' task as an objective for an evolutionary approach that starts from scratch without pre-shaped controller software or any other informed approach that would force the behavior to be evolved in a desired way.
A Robot to Shape your Natural Plant: The Machine Learning Approach to Model and Control Bio-Hybrid Systems
The evolved controllers augment the plants' natural light-finding and tissue-stiffening behaviors to avoid obstacles and grow desired shapes.
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.
"If you could see me through my eyes": Predicting Pedestrian Perception
In a preliminary study, we use synthetic data from simulations of a specific pedestrian crossing scenario to train a variational autoencoder and a long short-term memory network to predict a pedestrian's future visual perception.
Estimation of continuous environments by robot swarms: Correlated networks and decision-making
Collective decision-making is an essential capability of large-scale multi-robot systems to establish autonomy on the swarm level.
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.
Automatic Classification of Subjective Time Perception Using Multi-modal Physiological Data of Air Traffic Controllers
In this study, we present a method to automatically assess the subjective time perception of air traffic controllers, a group often faced with demanding conditions, using their physiological data and eleven state-of-the-art machine learning classifiers.
