The paper presents a framework called ECOS for Evolving COnnectionist Systems. ECOS evolve through incremental learning. They can accommodate any new input data, including new fea...
This paper investigates the combination of different neural network topologies for probabilistic feature extraction. On one hand, a five-layer neural network used in bottle neck f...
STRACTION FOR DISCRETE EVENT SYSTEMS USING NEURAL NETWORKS AND SENSITIVITY INFORMATION Christos G. Panayiotou Christos G. Cassandras Department of Manufacturing Engineering Boston ...
Christos G. Panayiotou, Christos G. Cassandras, We...
— In connectionist learning, one relevant problem is “catastrophic forgetting” that may occur when a network, trained with a large set of patterns, has to learn new input pat...
Dario Albesano, Roberto Gemello, Pietro Laface, Fr...
Abstract— A combination of backpropagation and neuroevolution is used to train a neural network visual controller for agents in the Quake II environment. The agents must learn to...