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Antifragile control systems in neuronal processing: A sensorimotor perspective
The stability--robustness--resilience--adaptiveness continuum in neuronal processing follows a hierarchical structure that explains interactions and information processing among the different time scales.
Antifragile Perimeter Control: Anticipating and Gaining from Disruptions with Reinforcement Learning
While previous research works have dedicated efforts to improving the robustness or resilience of transportation systems against disruptions, this paper applies the cutting-edge concept of antifragility to better design a traffic control strategy for urban road networks.
The Fragile Nature of Road Transportation Systems
The continuous increase in traffic demand presents a substantial challenge to the optimal operation of urban road networks and the efficiency of traffic control strategies.
Antifragility as a complex system's response to perturbations, volatility, and time
Antifragility characterizes the benefit of a dynamical system derived from the variability in environmental perturbations.
Recipes for calibration and validation of agent-based models in cancer biomedicine
Computational models and simulations are not just appealing because of their intrinsic characteristics across spatiotemporal scales, scalability, and predictive power, but also because the set of problems in cancer biomedicine that can be addressed computationally exceeds the set of those amenable to analytical solutions.
Antifragile Control Systems: The case of an oscillator-based network model of urban road traffic dynamics
In our work, we consider a novel system for road traffic control based on a network of interacting oscillators.
A Framework for Learning Invariant Physical Relations in Multimodal Sensory Processing
We design a novel neural network architecture capable of learning, in an unsupervised manner, relations among multiple sensory cues.
