This chapter explores the state of the emerging practice of designing markets by the use of agent-based modeling, with special reference to electricity markets and computerized (on-line) markets, perhaps including real-life electronic agents as well as human traders. The paper first reviews the...

In this paper, we examine an agent-based model and an equation-based model in the form of a mean field model. We show how the mean field model is a small, fast model that identifies the high level properties of a subject, in this case financial time series’ stylized facts. The agent based...

A genetic algorithm is convergent when genetic mutations occur on the objective function gradient direction. These genetic mutations are called genetic acquisitions (Mateescu, 2005). We improved the algorithm and its implementation by using the characteristics of parents in order to generate new...

We use minority game model to investigate evolutionary dynamics in complex networks of adaptive agents competing for limited resources. We show that the dynamics and the associated phase structures critically depend on the underlying network organizations, and evolution is a key mechanism for...

This paper examines the behavior of adaptive agents in a stochastic dynamic version of the Hotelling's location model. We conduct an innovative agent-based simulation under the Hotelling's setting with two agents who use the Nash Q-learning mechanism for adaptation. This allows us to explore...

A new algorithm for calibrating agent-based models is proposed, which employs a popular gradient boosting framework. Machine learning techniques are not used to develop a surrogate model, but rather assist in narrowing down the parameter space during the search for optimal parameters. Our...

This research aims to investigate, through simulation models, how the interaction among agents in an artificial stock market can affect the dynamics of asset prices. Thus, the study follows a different methodology for the analysis of prices by exploring the simulation of agents' behavior in an...

We propose a distributed randomized policy iteration algorithm for infinite horizon dynamic programming problems for which the control at each stage is m-dimensional. The traditional policy iteration algorithm involves performing a minimization over an m-dimensional constraint set and has a...

We are interested in how the relationship between the fee in a constant product market (CPM) and the volatility of the swapped pair on other liquid exchanges influences the losses / gains of the liquidity providers. We review three classical market making models: Glosten and Milgrom, Kyle and...

We propose a distributed randomized policy iteration algorithm for infinite horizon dynamic programming problems for which the control at each stage is m-dimensional. The traditional policy iteration algorithm involves performing a minimization over an m-dimensional constraint set and has a...