Particularity
Particularity
We describe a design principle for adaptive systems under which adaptation is driven by particular challenges that the environment poses, as opposed to average or otherwise aggregated measures of performance over many challenges. We trace the development of this "particularity" approach from the use of lexicase selection in genetic programming to "particularist" approaches to other forms of machine learning and to the design of adaptive systems more generally.
Genetic Programming Theory and Practice XX
- University of Massachusetts System United States
- UNIVERSITY OF MASSACHUSETTS United States
- Amherst College United States
I.2.2, FOS: Computer and information sciences, Computer Science - Machine Learning, Artificial Intelligence (cs.AI), Computer Science - Artificial Intelligence, I.2.6, Computer Science - Neural and Evolutionary Computing, Neural and Evolutionary Computing (cs.NE), I.2.2; I.2.6, Machine Learning (cs.LG)
I.2.2, FOS: Computer and information sciences, Computer Science - Machine Learning, Artificial Intelligence (cs.AI), Computer Science - Artificial Intelligence, I.2.6, Computer Science - Neural and Evolutionary Computing, Neural and Evolutionary Computing (cs.NE), I.2.2; I.2.6, Machine Learning (cs.LG)
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