Accession Number:

ADA270600

Title:

A Distributed Reinforcement Learning Scheme for Network Routing

Descriptive Note:

Corporate Author:

CARNEGIE-MELLON UNIV PITTSBURGH PA SCHOOL OF COMPUTER SCIENCE

Personal Author(s):

Report Date:

1993-07-01

Pagination or Media Count:

8.0

Abstract:

In this paper we describe a self-adjusting algorithm for packet routing, ill which a reinforcement learning module is embedded into each node of a switching network. Only local communication is used to keep accurate statistics at each node on which routing policies lead to minimal delivery times, In simple experiments involving a 36-node, irregularly connected network, this learning approach proves superior to a nonadaptive algorithm based on precomputed shortest paths.

Subject Categories:

  • Computer Systems

Distribution Statement:

APPROVED FOR PUBLIC RELEASE