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Found 19 papers, 2 papers with code
The Origin of Information Handling
A major challenge when describing the origin of life is to explain how instructional information control systems emerge naturally and spontaneously from mere molecular dynamics.
Quaternion Convolutional Neural Networks: Current Advances and Future Directions
Despite encouraging results, theoretical analysis shows that representations such as hyper-complex numbers can achieve richer representational capacities than real numbers, and that Hamilton products can capture intrinsic interchannel relationships.
Statistical analysis of word flow among five Indo-European languages
We study what we define as ``migrant words'', a type of loanwords that do not change their spelling.
Language statistics at different spatial, temporal, and grammatical scales
In this work, we use data from Twitter to explore English and Spanish considering the rank diversity at different scales: temporal (from 3 to 96 hour intervals), spatial (from 3km to 3000+km radii), and grammatical (from monograms to pentagrams).
Temporal Heterogeneity Improves Speed and Convergence in Genetic Algorithms
These algorithms simulate natural selection to explore a parameter space in search of solutions for a broad variety of problems.
Intelligence as information processing: brains, swarms, and computers
There is no agreed definition of intelligence, so it is problematic to simply ask whether brains, swarms, computers, or other systems are intelligent or not.
Artificial life: sustainable self-replicating systems
Nature has found one method of organizing living matter, but maybe other options exist -- not yet discovered -- on how to create life.
Stocks and Cryptocurrencies: Anti-fragile or Robust?
In this work we use our antifragility measure to analyze real data from return prices in the stock and cryptocurrency markets.
Antifragility Predicts the Robustness and Evolvability of Biological Networks through Multi-class Classification with a Convolutional Neural Network
Thus, we conclude that our antifragility measure can be used as a predictor of the robustness and evolvability of biological networks.
Self-Organization and Artificial Life
Placed at the frontiers between disciplines, Artificial Life (ALife) has heavily borrowed concepts and tools from the study of self-organization, providing mechanistic interpretations of life-like phenomena as well as useful constructivist approaches to artificial system design.
Self-Organization and Artificial Life: A Review
Self-organization has been an important concept within a number of disciplines, which Artificial Life (ALife) also has heavily utilized since its inception.
When slower is faster
The slower is faster (SIF) effect occurs when a system performs worse as its components try to do better.
Rank diversity of languages: Generic behavior in computational linguistics
We calculate this diversity for books published in six European languages since 1800, and find that it follows a universal lognormal distribution.
Complexity measurement of natural and artificial languages
We compared entropy for texts written in natural languages (English, Spanish) and artificial languages (computer software) based on a simple expression for the entropy as a function of message length and specific word diversity.
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.
Measuring the Complexity of Ultra-Large-Scale Adaptive Systems
Here we propose the design and analysis of ULS systems using measures of complexity, emergence, self-organization, and homeostasis based on information theory.
Self-organizing traffic lights: A realistic simulation
We have previously shown in an abstract simulation (Gershenson, 2005) that self-organizing traffic lights can improve greatly traffic flow for any density.
Artificial Neural Networks for Beginners
The scope of this teaching package is to make a brief induction to Artificial Neural Networks (ANNs) for people who have no previous knowledge of them.
