Abstract | ||
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Evolvable Hardware (EHW) has been proposed as a new technique to design complex systems. Often, complex systems turn out to be very difficult to evolve. The problem is that a general strategy is too difficult for the evolution process to discover directly. This paper proposes a new approach that performs incremental evolution in two directions: from complex system to sub-systems and from subsystems back to complex system. In this approach, incremental evolution gradually decomposes a complex problem into some sub-tasks. In a second step, we gradually make the tasks more challenging and general. Our approach automatically discovers the sub-tasks, their sequence as well as circuit layout dimensions. Our method is tested in a digital circuit domain and compared to direct evolution. We show that our bidirectional incremental approach can handle more complex, harder tasks and evolve them more effectively, then direct evolution. |
Year | DOI | Venue |
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2000 | 10.1109/EH.2000.869343 | Evolvable Hardware |
Keywords | Field | DocType |
bidirectional incremental approach,evolution process,complex system,extrinsic evolvable hardware,general strategy,bidirectional incremental evolution,new approach,incremental evolution,circuit layout dimension,digital circuit domain,direct evolution,complex problem,digital circuits,genetic algorithms,hardware,directed evolution,robots,neural networks,stochastic processes | Complex system,Digital electronics,Computer science,Stochastic process,Evolvable hardware,Artificial intelligence,Artificial neural network,Robot,Genetic algorithm | Conference |
ISBN | Citations | PageRank |
0-7695-0762-X | 50 | 2.11 |
References | Authors | |
9 | 1 |
Name | Order | Citations | PageRank |
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Tatiana Kalganova | 1 | 195 | 15.96 |