Continuous space language models
Computer Speech and Language
Fast Evaluation of Connectionist Language Models
IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part I: Bio-Inspired Systems: Computational and Ambient Intelligence
UCH-UPV English: Spanish system for WMT10
WMT '10 Proceedings of the Joint Fifth Workshop on Statistical Machine Translation and MetricsMATR
CEU-UPV English-Spanish system for WMT11
WMT '11 Proceedings of the Sixth Workshop on Statistical Machine Translation
A hybrid approach to statistical language modeling with multilayer perceptrons and unigrams
TSD'05 Proceedings of the 8th international conference on Text, Speech and Dialogue
Hi-index | 0.00 |
This paper deals with the introduction of long term memory in a Multilevel Darwinist Brain (MDB) structure based on Artificial Neural Networks and its implications on the capability of adapting to new environments and recognizing previously explored ones by autonomous robots. The introduction of long term memory greatly enhances the ability of the organisms that implement the MDB to deal with changing environments and at the same time recover from failures and changes in configurations. The paper describes the mechanism, introduces the long term mermoy within it and provides some examples of its operation both in theoretical problems and on a real robot whose perceptual and actuation mechanisms are changed periodically.