Arthur C. Sanderson

Artificial Intelligence · 1999–2009

A researcher in the Science corpus: 3 papers; trusts 19 researchers and is trusted by 52 researchers here, as inferred from the citation graph.

Subfields

Whom Arthur C. Sanderson trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

  1. Xin Yao
  2. Hussein A. Abbass
  3. Jason Teo
  4. Robert A. Ghanea-Hercock
  5. Ioan Cristian Trelea
  6. David E. Goldberg
  7. A. K. Qin
  8. Junhong Liu
  9. Zhenyu Yang
  10. Kalyanmoy Deb

Who trusts Arthur C. Sanderson overall

  1. Pinar Çivicioglu
  2. Wenyin Gong
  3. Ryoji Tanabe
  4. Weifeng Gao
  5. Swagatam Das
  6. Zhihua Cai
  7. Ponnuthurai Nagaratnam Suganthan
  8. Ran Cheng
  9. Alex S. Fukunaga
  10. James Jian Qiao Yu

Papers from Arthur C. Sanderson's perspective

Ordered by how strongly the researchers Arthur C. Sanderson trusts endorse each paper. Same corpus, a different order for every researcher.

  1. A fast and elitist multiobjective genetic algorithm: NSGA-II
  2. Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces
  3. Parameter Control in Evolutionary Algorithms
  4. Self-adaptive differential evolution algorithm for numerical optimization (IEEE Congress on Evolutionary Computation)
  5. A comparative study of differential evolution, particle swarm optimization, and evolutionary algorithms on numerical benchmark problems (Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753))
  6. Evolutionary algorithms in theory and practice - evolution strategies, evolutionary programming, genetic algorithms
  7. The self-adaptive Pareto differential evolution algorithm (Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600))
  8. Evolutionary programming made faster
  9. Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence
  10. Evolutionary programming using mutations based on the Levy probability distribution (IEEE Transactions on Evolutionary Computation)

Their papers