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Found 7 papers, 1 papers with code
Beehive scale-free emergent dynamics
It has been repeatedly reported that the collective dynamics of social insects exhibit universal emergent properties similar to other complex systems.
On the use of associative memory in Hopfield networks designed to solve propositional satisfiability problems
Hopfield networks are an attractive choice for solving many types of computational problems because they provide a biologically plausible mechanism.
Scaling up the self-optimization model by means of on-the-fly computation of weights
The Self-Optimization (SO) model is a useful computational model for investigating self-organization in "soft" Artificial life (ALife) as it has been shown to be general enough to model various complex adaptive systems.
The distribution of inhibitory neurons in the C. elegans connectome facilitates self-optimization of coordinated neural activity
The nervous system of the nematode soil worm Caenorhabditis elegans exhibits remarkable complexity despite the worm's small size.
Neural coordination can be enhanced by occasional interruption of normal firing patterns: A self-optimizing spiking neural network model
In addition, by using this spiking neural network to emulate a Hopfield network with Hebbian learning, we attempt to make a connection between rate-based and temporal coding based neural systems.
Motility at the origin of life: Its characterization and a model
On this view, self-movement, adaptive behavior and morphological changes could have already been present at the origin of life.
The Dynamically Extended Mind -- A Minimal Modeling Case Study
A prominent critique of this claim holds that when some part of the world is coupled to a cognitive system this does not necessarily entail that the part is also constitutive of that cognitive system.
