Explainability and Graph Learning From Social Interactions

willingness to communicate in the iranian context: language learning orientation and social support

why some learners are willing to communicate in english, concurrently others are not, has been an intensive investigation in l2 education. willingness to communicate (wtc) proposed as initiating to communicate while given a choice has recently played a crucial role in l2 learning. it was hypothesized that wtc would be associated with language learning orientations (llos) as well as social suppo...

Social Learning with Local Interactions

We study a simple dynamic model of social learning with local informational externalities. There is a large population of agents, who repeatedly have to choose one, out of two, reversible actions, each of which is optimal in one, out of two, unknown states of the world. Each agent chooses rationally, on the basis of private information (s)he receives by a symmetric binary signal on the state, a...

Learning social interactions between agents

Sampling from social networks’s graph based on topological properties and bee colony algorithm

In recent years, the sampling problem in massive graphs of social networks has attracted much attention for fast analyzing a small and good sample instead of a huge network. Many algorithms have been proposed for sampling of social network’ graph. The purpose of these algorithms is to create a sample that is approximately similar to the original network’s graph in terms of properties such as de...

From Machine Ethics To Machine Explainability and Back

We find ourselves surrounded by a rapidly increasing number of autonomous and semi-autonomous systems. Two grand challenges arise from this development: Machine Ethics and Machine Explainability. Machine Ethics, on the one hand, is concerned with behavioral constraints for systems, set up in a formal unambiguous, algorithmizable, and implementable way, so that morally acceptable, restricted beh...