recent research it has become increasingly clear that, to boost the
principled exploration of viable and powerful Artificial Intelligence (AI)
strategies, particularly for robotics and autonomous agents, a strong
incentive derives from using adequate scenarios. Suitable scenarios usually
display different aspects or levels at which a problem has to be solved,
where an increasing number of new levels unfold on closer inspection and the
different levels also interact with each other. This is one of the implicit
reasons for the popularity of Embodied Robotics as opposed to simulated
autonomous agent environments.
It turns out that the use of competitive multiagent scenarios allows to
vigorously reintroduce this aspect into simulation studies while at the same
time taking additional advantage of the specific possibilities offered in
simulated environments, e.g. reproducibility, controllability' and monitoring
The talk will introduce paradigmatic examples of such scenarios e.g. ant
colonies and robotic soccer), discuss selected AI challenges posed by them
and present approaches to tackle these challenges.