We introduce and motivate a non-standard multi-modal logic to represent and reason about ignorance in Multi-Agent Systems. We argue that in Multi-agent systems being able to reaso...
Abstract. We propose a machine learning approach to action prediction in oneshot games. In contrast to the huge literature on learning in games where an agent's model is deduc...
Debugging multi-agent systems, which are concurrent, distributed, and consist of complex components, is difficult, yet crucial. In earlier work we have proposed mechanisms whereby...
We explore the problem of specification and verification of compliance in agent based Web service compositions. We use the formalism of temporal-epistemic logic suitably extended ...
We initiate the study of incentives in a general machine learning framework. We focus on a game-theoretic regression learning setting where private information is elicited from mu...