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2010
Springer

Combining Software and Hardware LCS for Lightweight On-Chip Learning

8 years 6 months ago
Combining Software and Hardware LCS for Lightweight On-Chip Learning
In this paper we present a novel two-stage method to realize a lightweight but very capable hardware implementation of a Learning Classifier System for on-chip learning. Learning Classifier Systems (LCS) allow taking good run-time decisions, but current hardware implementations are either large or have limited learning capabilities. In this work, we combine the capabilities of a software-based LCS, the XCS, with a lightweight hardware implementation, the LCT, retaining the benefits of both. We compare our method with other LCS implementations using the multiplexer problem and evaluate it with two chiprelated problems, run-time task allocation and SoC component parameterization. In all three problem sets, we find that the learning and selfadaptation capabilities are comparable to a full-fledged system, but with the added benefits of a lightweight hardware implementation, namely small area size and quick response time. Given our work, autonomous chips based on Learning Classifier Systems...
Andreas Bernauer, Johannes Zeppenfeld, Oliver Brin
Added 18 May 2011
Updated 18 May 2011
Type Journal
Year 2010
Where IFIP
Authors Andreas Bernauer, Johannes Zeppenfeld, Oliver Bringmann, Andreas Herkersdorf, Wolfgang Rosenstiel
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