A longstanding problem in the social, biological, and computational sciences is to determine
how groups of distributed individuals can form intelligent collective judgments. Since …

Motivated by emerging need of learning algorithms for large scale networked and
decentralized systems, we introduce a distributed version of the classical stochastic Multi …

Swarm intelligence (SI) is a collective behaviour exhibited by groups of simple agents, such
as ants, bees, and birds, which can achieve complex tasks that would be difficult or …

Researchers across cognitive science, economics, and evolutionary biology have studied
the ubiquitous phenomenon of social learning—the use of information about other people's …

In this work, we introduce an innovative Markov Chain Monte Carlo (MCMC) classifier, a
synergistic combination of Bayesian machine learning and Apache Spark, highlighting the …

The Rooney Rule, originally proposed to counter implicit bias in hiring, has been
implemented in the private and public sector in various settings. This rule requires that a …

This paper outlines some provisional steps toward a theory of culture grounded in
computational thinking. I begin by describing computational thinking, drawing on Marr's …

The potential of an efficient ride‐sharing scheme to significantly reduce traffic congestion,
lower emission level, and drivers' stress, as well as facilitating the introduction of smart cities …

Widespread rumoring can hinder attempts to make sense of what is going on during disaster
scenarios. Understanding how and why rumors spread in these contexts could assist in the …

Many of the computational problems people face are difficult to solve under the limited time
and cognitive resources available to them. Overcoming these limitations through social …