We analyze a coordination game with information-constrained players. The players' actions are based on a noisy compressed representation of the game's payoffs in a particular case, where the compressed representation is a latent state learned by a variational autoencoder (VAE). Our generalized...

This paper models the learning process of populations of randomly rematched tabula rasa neural network (NN) agents playing randomly generated 2x2 normal form games of all strategic classes. This approach has greater external validity than the existing models in the literature, each of which is...

This paper addresses the question of whether neural networks (NNs), a realistic cognitive model of human information processing, can learn to backward induce in a two-stage game with a unique subgame-perfect Nash equilibrium. The NNs were found to predict the Nash equilibrium approximately 70%...

This paper addresses how neural networks learn to play one-shot normal form games through experience in an environment of randomly generated game payoffs and randomly selected opponents. This agent based computational approach allows the modeling of learning all strategic types of normal form...

Replicator dynamics and replication as used in evolutionary algorithms are, due to their most basic forms, structurally the same. This short note will prove this thesis. Although this finding is clear cut and easy to show, it is of great importance for the not yet united families of game...

One of the most famous ranking methods for digraphs is the ranking by Copeland score. The Copeland score of a node in a digraph is the difference between its outdegree (i.e. its number of outgoing arcs) and its indegree (i.e. its number of ingoing arcs). In the ranking by Copeland score, a node...

In this paper, we connect the social network theory on centrality measures to the economic theory of preferences and utility. Using the fact that networks form a special class of cooperative TU-games, we provide a foundation for the degree measure as a von Neumann-Morgenstern expected utility...

The idiosyncratic (microscopic) and systemic (macroscopic) components of market structure have been shown to be responsible for the departure of the optimal mean-variance allocation from the heuristic 'equally-weighted' portfolio. In this paper, we exploit clustering techniques derived from...

This paper aims to connect the social network literature on centrality measures with the economic literature on von Neumann-Morgenstern expected utility functions using cooperative game theory. The social network literature studies various concepts of network centrality, such as degree,...

We present an analytical solution for the connectivity of a network model with a "non-simultaneous" linking scheme. Despite its simplicity, this model exhibits node-space correlations in the link distribution, and anomalous fluctuations behavior of the time series of the connectivity variable,...