This paper evaluates and compares the performance of two approaches for locating an agent in a mobile agent environment. The first approach dynamically creates a chain of forwarde...
In this paper, we present Reo2MC, a tool chain for the performance evaluation of coordination models. Given a coordination model represented by a stochastic Reo connector, Reo2MC ...
Farhad Arbab, Sun Meng, Young-Joo Moon, Marta Z. K...
The most commonly used learning algorithm for restricted Boltzmann machines is contrastive divergence which starts a Markov chain at a data point and runs the chain for only a few...
In this paper, we formulate agent's decision process under the framework of Markov decision processes, and in particular, the multi-agent extension to Markov decision process...
In this paper, we develop a new "robust mixing" framework for reasoning about adversarially modified Markov Chains (AMMC). Let P be the transition matrix of an irreducib...