Classically, an approach to the multiagent policy learning supposed that the agents, via interactions and/or by using preliminary knowledge about the reward functions of all playe...
Combinatorial auctions where agents can bid on bundles of items are desirable because they allow the agents to express complementarity and substitutability between the items. Howe...
We propose a novel, supervised feature extraction procedure, based on an unbiased estimator of the Hilbert-Schmidt independence criterion (HSIC). The proposed procedure can be dire...
This paper presents a multiagent architecture constructed for learning from the interaction between the atmosphere and the ocean. The ocean surface and the atmosphere exchange carb...
We present an axiomatisation for an extension of a temporal epistemic logic with an epistemic “reset” operator defined on the intersection between epistemic and temporal rela...