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pro vyhledávání: '"Kavitesh Kumar, Bali"'
Publikováno v:
In Intelligence-Based Medicine 2022 6
Publikováno v:
IEEE Transactions on Cybernetics. 51:1784-1796
Humans have the ability to identify recurring patterns in diverse situations encountered over a lifetime, constantly understanding relationships between tasks and efficiently solving them through knowledge reuse. The capacity of artificial intelligen
Publikováno v:
IEEE Transactions on Evolutionary Computation. 24:69-83
Humans rarely tackle every problem from scratch. Given this observation, the motivation for this paper is to improve optimization performance through adaptive knowledge transfer across related problems. The scope for spontaneous transfers under the s
Publikováno v:
CEC
Recent analytical studies have revealed that in spite of promising success in problem solving, the performance of evolutionary multitasking deteriorates with decreasing similarity between constitutive tasks. The present day multifactorial evolutionar
Publikováno v:
CEC
Competition in cooperative coevolution (CC) has demonstrated success in solving global optimization problems. In a recent study, a multi-island competitive cooperative coevolution (MIC3) algorithm was introduced that featured competition and collabor
Publikováno v:
CEC
Problem decomposition determines how subcomponents are created that have a vital role in the performance of cooperative coevolution. Cooperative coevolution naturally appeals to fully separable problems that have low interaction amongst subcomponents
Autor:
Rohitash Chandra, Kavitesh Kumar Bali
Publikováno v:
CEC
Cooperative coevolution has proven to be efficient in solving global optimisation and real world application problems. However, it is highly sensitive to problem decomposition, especially in the context of non-separable functions that possess interac
Autor:
Kavitesh Kumar Bali, Rohitash Chandra
Publikováno v:
Neural Information Processing ISBN: 9783319265544
ICONIP (3)
ICONIP (3)
Problem decomposition is an important attribute of cooperative coevolution that depends on the nature of the problems in terms of separability which is defined by the level of interaction amongst decision variables. Recent work in cooperative coevolu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ddde7725438614062835f62d78cebbfb
https://doi.org/10.1007/978-3-319-26555-1_15
https://doi.org/10.1007/978-3-319-26555-1_15
Autor:
Rohitash Chandra, Kavitesh Kumar Bali
Publikováno v:
AI 2015: Advances in Artificial Intelligence ISBN: 9783319263496
Australasian Conference on Artificial Intelligence
Australasian Conference on Artificial Intelligence
A major challenge in using cooperative coevolution (CC) for global optimisation is the decomposition of a given problem into subcomponents. Variable interaction is a major constraint that determines the decomposition strategy of a problem. Hence, fin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a275507d063f4d6450f85c4aca508ee4
https://doi.org/10.1007/978-3-319-26350-2_4
https://doi.org/10.1007/978-3-319-26350-2_4