Traditional agent-based modelling is mostly rule-based. For many systems, this approach is
extremely successful, since the rules are well understood. However, for a large class of …

Agent-based modelling is a powerful tool when simulating human systems, yet when human
behaviour cannot be described by simple rules or maximizing one's own profit, we quickly …

Over the last two decades, with advances in computational availability and power, we have
seen a rapid increase in the development and use of Machine Learning (ML) solutions …

Agent-based modelling is a successful technique in many different fields of science. As a
bottom-up method, it is able to simulate complex behaviour based on simple rules and show …

In this paper we propose a strategy learning model for autonomous agents based on
classification. In the literature, the most commonly used learning method in agent-based …

We offer a novel approach to agent-based economic modeling. Previous work has modeled
learning agents as neural networks, sets of fuzzy rules and other learning algorithms. In this …

Designing the proper agent behavior for a multiagent system is a complex task. Often it is not
obvious which of the agents' actions, and the interactions among them and with their …

This document is the main result of the master's thesis project I performed, at the final stage
of the master's programme System Engineering, Policy Analysis and Management at the …

We present a formalization of the Recursive Modeling Method, which we have previously,
somewhat informally, proposed as a method that autonomous artificial agents can use for …

Abstract Agent-Based Models (ABM) are being increasingly applied to the study of a wide
range of social phenomena, often putting the focus on the macroscopic patterns that emerge …