We present methods for an autonomous agent to identify dominant market conditions, such as over-supply or scarcity, and to predict market changes. The characteristics of economic regimes are learned from historic data and used, together with real-time observable information, to identify the current market regime and to forecast market changes. We use a Gaussian Mixture Model to represent the pr...

Agents must form and update mental models about each other in a wide range of domains: team coordination, plan recognition, social simulation, user modeling, games of incomplete information, etc. Existing research typically treats the problem of forming beliefs about other agents as an isolated subproblem, where the modeling agent starts from an initial set of possible models for another agent ...

In order to reduce the complexity of large knowledge-based systems and promote reusability, means for decomposing them to smaller chunks are required. MIKE, our knowledge engineering framework, provides three basic means for structuring which are described in this paper: different kinds of knowledge are separated at different knowledge layers, knowledge layers can be structured by modules, and ...

Model-driven engineering (MDE) is an approach for improving productivity in software development. This approach was exploited in the context of agent-based modeling and simulation (ABMS) only to a certain extent. Previous work has not shown real evidence of the benefits that MDE promotes in ABMS. This paper thus explores the use of MDE in ABMS with a case study in the traffic domain. We propose...

Large display environments allow to support collective visualization of Virtual Reality applications. As interaction in those environments can be troublesome, we considered the integration of gestural information into corresponding interaction techniques. To get rid of trackers and of some of the typical devices weaknesses, we investigated the use of video tracking. The realtime system we propo...

We study a linear threshold agent-based model (ABM) for the spread of political revolutions on social networks using empirical network data. We propose new techniques for building a hierarchy of simplified ordinary differential equation (ODE) based models that aim to capture essential features of the ABM, including effects of the actual networks, and give insight in the parameter regime transit...