What is recorded here?
Presented NEAT, which evolves neural-network weights and topology together through historical markings, speciation and incremental complexification, and evaluated the components on a reinforcement-learning benchmark.
Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.
Scientific scope
The record is the exact two-author 2002 Evolutionary Computation article. Its benchmark evidence is not universal superiority, and later HyperNEAT, novelty search and other neuroevolution systems remain separate.
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People and systems
Kenneth O. Stanley; Risto Miikkulainen
The named authors contributed to this scoped work; individual effort shares and later applications are not assigned by the byline.
Research locations and affiliations
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Documented countries / regions: United States
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English catalogue narrative
Stanley and Miikkulainen: NeuroEvolution of Augmenting Topologies
Presented NEAT, which evolves neural-network weights and topology together through historical markings, speciation and incremental complexification, and evaluated the components on a reinforcement-learning benchmark.
Scientific scope
The record is the exact two-author 2002 Evolutionary Computation article. Its benchmark evidence is not universal superiority, and later HyperNEAT, novelty search and other neuroevolution systems remain separate.
Reading status
This is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.
People and systems
Kenneth O. Stanley; Risto Miikkulainen
The named authors contributed to this scoped work; individual effort shares and later applications are not assigned by the byline.