Evolving reactive agents with SignalGP
- Published
- Accepted
- Subject Areas
- Adaptive and Self-Organizing Systems, Agents and Multi-Agent Systems, Artificial Intelligence
- Keywords
- evolutionary computation, genetic programming, SignalGP, event-driven programming, tags
- Copyright
- © 2018 Lalejini et al.
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
- Cite this article
- 2018. Evolving reactive agents with SignalGP. PeerJ Preprints 6:e26921v1 https://doi.org/10.7287/peerj.preprints.26921v1
Abstract
We introduce SignalGP, a technique for creating digital organisms that harnesses the event-driven programming paradigm. These organisms can evolve to automatically react to signals from the environment or from other agents in a biologically-inspired manner. In addition to introducing SignalGP, we summarize previous results demonstrating the value of the event-driven paradigm in environments dominated by agent-agent and agent-environment interaction. Our full introduction to SignalGP will be published in the proceedings of the 2018 Genetic and Evolutionary Computation Conference (pre-print: https://arxiv.org/pdf/1804.05445.pdf).
Author Comment
This submission is a peer-reviewed extended abstract to appear in the proceedings of 2018 Conference on Artificial Life (ALIFE). In this extended abstract, we introduce SignalGP to the Artificial Life community, summarizing our full introduction to SignalGP (pre-print: https://arxiv.org/pdf/1804.05445.pdf).