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- W1569657319 abstract "In this paper, we describe a parallel processing architecture for Evolvable Hardware (EHW) which changes its own hardware structure in order to adapt to the environment in which it is embedded. This adaptation process is a combination of genetic learning with reinforcement learning. As an example of EHW applications, the arbitration in behavior-based robot is discussed. Our goal by implementing adaptation in hardware is to produce a flexible and fault-tolerant architecture which responds in real-time to a changing environment." @default.
- W1569657319 created "2016-06-24" @default.
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- W1569657319 date "1994-01-01" @default.
- W1569657319 modified "2023-10-04" @default.
- W1569657319 title "Applying Evolvable Hardware to autonomous agents" @default.
- W1569657319 cites W1487663223 @default.
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- W1569657319 doi "https://doi.org/10.1007/3-540-58484-6_295" @default.
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