Verkauf durch Sack Fachmedien

Touretzky

Connectionist Approaches to Language Learning

Medium: Buch
ISBN: 978-0-7923-9216-3
Verlag: Springer Us
Erscheinungstermin: 30.09.1991
Lieferfrist: bis zu 10 Tage

arise automatically as a result of the recursive structure of the task and the continuous nature of the SRN's state space. Elman also introduces a new graphical technique for study­ ing network behavior based on principal components analysis. He shows that sentences with multiple levels of embedding produce state space trajectories with an intriguing self­ similar structure. The development and shape of a recurrent network's state space is the subject of Pollack's paper, the most provocative in this collection. Pollack looks more closely at a connectionist network as a continuous dynamical system. He describes a new type of machine learning phenomenon: induction by phase transition. He then shows that under certain conditions, the state space created by these machines can have a fractal or chaotic structure, with a potentially infinite number of states. This is graphically illustrated using a higher-order recurrent network trained to recognize various regular languages over binary strings. Finally, Pollack suggests that it might be possible to exploit the fractal dynamics of these systems to achieve a generative capacity beyond that of finite-state machines.


Produkteigenschaften


  • Artikelnummer: 9780792392163
  • Medium: Buch
  • ISBN: 978-0-7923-9216-3
  • Verlag: Springer Us
  • Erscheinungstermin: 30.09.1991
  • Sprache(n): Englisch
  • Auflage: 1991. Auflage 1991
  • Serie: The Springer International Series in Engineering and Computer Science
  • Produktform: Gebunden
  • Gewicht: 399 g
  • Seiten: 149
  • Format (B x H x T): 156 x 234 x 11 mm
  • Ausgabetyp: Kein, Unbekannt
Autoren/Hrsg.

Herausgeber

Learning Automata from Ordered Examples.- SLUG: A Connectionist Architecture for Inferring the Structure of Finite-State Environments.- Graded State Machines: The Representation of Temporal Contingencies in Simple Recurrent Networks.- Distributed Representations, Simple Recurrent Networks, and Grammatical Structure.- The Induction of Dynamical Recognizers.