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Achieving Long-Term Progress in Competitive Co-Evolution

Chapter
Publication Date:
2017
abstract:
We illustrate how co-evolutionary experiments involving simulated predator and prey robots can lead to long-term global progress, i.e. can produce robots displaying progressively better performance against both competitors of current and previous generations. This is obtained by exposing evolving robots to well-differentiated competitors, by preserving individuals displaying good performance against hard to handle competitors, and by discarding opportunistic individuals that perform poorly against the other competitors of the current generation. The accumulation of variations producing general progress for more than 50,000 generations leads to the evolution of sophisticated behavioral capabilities and enable evolved robots to outperform robots evolved with simpler methods.
Iris type:
02.01 Contributo in volume (Capitolo o Saggio)
Keywords:
competitive co-evolution; long-term progress; arm-races
List of contributors:
Simione, Luca; Nolfi, Stefano
Authors of the University:
NOLFI STEFANO
SIMIONE LUCA
Handle:
https://iris.cnr.it/handle/20.500.14243/344915
Book title:
Proceedings of IEEE Symposium Series on Computational Intelligence
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https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8280898
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