We address several challenges for applying statistical dialog managers based on Partially Observable Markov Models to real world problems: to deal with large numbers of concepts, ...
Sebastian Varges, Giuseppe Riccardi, Silvia Quarte...
The main purpose of this paper is to propose a Multi-Agent Autonomic and Bio-Inspired based framework with selfmanaging capabilities to solve complex scheduling problems using coo...
Many approaches of the agent paradigm emphasize the social and intentional features of their systems, what are called social properties. The study of these aspects demands their ow...
The Agent-Community-based Peer-to-Peer Information Retrieval (ACP2P) method uses agent communities to manage and look up information of interest to users. An agent works as a dele...
Spoken dialogue management strategy optimization by means of Reinforcement Learning (RL) is now part of the state of the art. Yet, there is still a clear mismatch between the comp...