Recent advancements in model-based reinforcement learning have shown that the dynamics of many structured domains (e.g. DBNs) can be learned with tractable sample complexity, desp...
Thomas J. Walsh, Sergiu Goschin, Michael L. Littma...
—Developing dependable distributed real-time and embedded (DRE) systems incurs significant complexities in the tradeoffs resulting from the different conflicting attributes of ...
Sumant Tambe, Akshay Dabholkar, Aniruddha S. Gokha...
Abstract. Engineering non-trivial open multi-agent systems is a challenging task. Our research focusses on situated multi-agent systems, i.e. systems in which agents are explicitly...
Although feature modelling is a frequently used approach to the task of modelling commonality and variability within product lines, there is currently no standard modelling notati...
T. John Brown, Rachel Gawley, Ivor T. A. Spence, P...
The initialisation of segmentation methods aiming at the localisation of biological structures in medical imagery is frequently regarded as a given precondition. In practice, howev...