This paper presents the design of an open architecture for heterogeneous negotiating agents. Both the system level architecture as well as the architecture for negotiating agents a...
Koen V. Hindriks, Catholijn M. Jonker, Dmytro Tykh...
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...
To be sociable, embodied interactive agents like virtual characters or humanoid robots need to be able to engage in mutual coordination of behaviors, beliefs, and relationships wit...
Stefan Kopp, Kirsten Bergmann, Hendrik Buschmeier,...
Abstract. The function of a protein is dependent on whether and how it can interact with various ligands. Therefore, an accurate prediction of protein-ligand interactions is paramo...
A recent report by the National Research Council (NRC) declares neural networks “hold the most promise for providing powerful learning models”. While some researchers have expe...
Amy E. Henninger, Avelino J. Gonzalez, Michael Geo...