Hugues Juille. Methods for Statistical Inference: Extending the Evolutionary Computation Paradigm. PhD thesis, Brandeis University, 1999. Home/Search Document Details and Download
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Pareto Optimality in Coevolutionary Learning - Sevan Ficici And (2001) (8 citations) (Correct)
....challenge it. We must wait until some variation occurs to generate a new learner that outperforms L # in some dimension(s) and creates new gaps in competence. This approach to creating and maintaining gradient for coevolutionary learning is substantially di#erent from those of Rosin [18] Juille [7], Olsson [15] and Paredis [16] 2.2 Learning: Following Gradient This section describes how we measure success at following a high dimensional gradient using the Pareto optimality concept. We name the set of learners R and the set of teachers S. The payo# matrix G describes the performance ....
.... ICs, and thereby arrive at an approach that should more easily generalize to other problem domains (e.g. sorting networks) Indeed, we intend ultimately to apply our Pareto coevolution methodology to variable sum games, in addition to zero sum games such as those studied by Rosin [18] and Juille [7]. While we do not improve upon the results of Juille and Pollack [10, 9] we improve significantly upon all results published elsewhere. The next most e#ective rule is by Andre, et al. [1] which performs at 82.4 . This rule was discovered with genetic programming in experiments using a rule ....
H. Juille. Methods for Statistical Inference: Extending the Evolutionary Computation Paradigm. PhD thesis, Brandeis University, 1999.
Learning the Ideal Evaluation Function - De Jong (2003) (Correct)
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Hugues Juille. Methods for Statistical Inference: Extending the Evolutionary Computation Paradigm. PhD thesis, Brandeis University, 1999.
The Incremental Pareto-Coevolution Archive - de Jong (2004) (1 citation) (Correct)
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Hugues Juille. Methods for Statistical Inference: Extending the Evolutionary Computation Paradigm. PhD thesis, Brandeis University, 1999.
Intransitivity in Coevolution - de Jong (Correct)
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Juille, H.: Methods for Statistical Inference: Extending the Evolutionary Computation Paradigm. PhD thesis, Brandeis University (1999)
Learning the Ideal Evaluation Function - Edwin De Jong (2003) (Correct)
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Hugues Juille. Methods for Statistical Inference: Extending the Evolutionary Computation Paradigm. PhD thesis, Brandeis University, 1999.
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