We develop a new graphical representation for interactive partially observable Markov decision processes (I-POMDPs) that is significantly more transparent and semantically clear t...
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...