We present an approach to use evolutionary learning of behavior to improve testing of
commercial computer games. After identifying unwanted results or behavior of the game, we …

We investigate possible improvements to modeling other agents based on observed
situation-action pairs and the nearest neighbor rule. Tentative stereotype models allow for …

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 …

Autonomous agents interacting in an open world can be considered to be primarily driven by
self interests. In this paper, we evaluate the hypotheses that self-interested agents with …

Autonomous agents interacting in an open world can be considered to be primarily driven by
self interests. Previous work in this area has prescribed a strategy of reciprocal behavior …

The typically large numbers of interactions in agent-based simulations come at considerable
computational costs. In this article, we present an approach to reduce the number of …

The widespread adoption of online learning has significantly transformed the dynamics of
cooperative learning. One of the main challenges in distance cooperative learning is …

We present a method to test a group of agents for (unwanted) emergent behavior by using
techniques from learning of cooperative behavior. The general idea is to mimick users or …

The game of Lemmings has been offered as a new Drosophila for AI research. Yet the
authors have no knowledge of any efforts to create a computer player for Lemmings. This …

Modelling natural processes requires the implementation of an expressive representation of
the involved entities and their interactions. We present swarm graph grammars (SGGs) as a …