A problem of planning for cooperative teams under uncertainty is a crucial one in multiagent systems. Decentralized partially observable Markov decision processes (DECPOMDPs) prov...
In this paper we propose a genetic programming approach to learning stochastic models with unsymmetrical noise distributions. Most learning algorithms try to learn from noisy data...
Abstract. This paper presents a prototype implementation of an intelligent assistance architecture for data-driven simulation specialising in qualitative data in the social science...
Catriona Kennedy, Georgios K. Theodoropoulos, Volk...
Abstract- This paper presents a RWA strategy based on the stochastic estimation of the Effective Number of Available Wavelengths (ENAW) along interdomain paths. We propose an appro...
The paper presents an efficient solution to decision problems where direct partial information on the distribution of the states of nature is available, either by observations of ...