We present an approach for secure information flow property preserving refinement and transformation of UML inspired interaction diagrams. The approach is formally underpinned b...
Modeling the perceived behaviors of other agents improves the performance of an agent in multiagent interactions. We utilize the language of interactive influence diagrams to mode...
Although research on non-visual access to visualisations is steadily growing, very little work has investigated strategies for constructing such forms of representation through no...
This paper extends the framework of dynamic influence diagrams (DIDs) to the multi-agent setting. DIDs are computational representations of the Partially Observable Markov Decisio...
Interactive dynamic influence diagrams (I-DIDs) are graphical models for sequential decision making in uncertain settings shared by other agents. Algorithms for solving I-DIDs fac...