Portfolio optimization has been a central problem in finance, often approached with two steps: calibrating the parameters and then solving an optimization problem. Yet, the two-step procedure sometimes encounter the ``error maximization'' problem where inaccuracy in parameter estimation...

This paper models the learning process of a population of randomly-rematched tabula rasa neural network agents playing randomly generated 3 × 3 normal form games of all strategic types. Evidence was found of the endogenous emergence of a similarity measure of games based on the number and types...

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%...

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...

The best shot game applied to networks is a discrete model of many processes of contribution to local public goods. It has generally a wide multiplicity of equilibria that we refine through stochastic stability. In this paper we show that, depending on how we define perturbations, i.e. the...

Our study analyzes theories of learning for strategic interactions in networks. Participants played two of the 2 x 2 games used by Selten and Chmura (2008) and in the comment by Brunner, Camerer and Goeree (2009). Every participant played against four neighbors and could choose a different...

Our study analyzes theories of learning for strategic interactions in networks. Participants played two of the 2 x 2 games used by Selten and Chmura (2008) and in the comment by Brunner, Camerer and Goeree (2009). Every participant played against four neighbors and could choose a different...

For games of simultaneous action selection and network formation, game-theoretic behavior and experimental observations are not in line: While theory typically predicts inefficient outcomes for (anti-)coordination games, experiments show that subjects tend to play efficient (non Nash) strategy...

The best shot game applied to networks is a discrete model of many processes of contribution to local public goods. It has generally a wide multiplicity of equilibria that we refine through stochastic stability. In this paper we show that, depending on how we define perturbations, i.e. the...

Our study analyzes theories of learning for strategic interactions in networks. Participants played two of the 2 x 2 games used by Selten and Chmura (2008). Every participant played against four neighbors and could choose a different strategy against each of them. The games were played in two...