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Definition of Edges: basin, escape, monotonic, crossovel Visualisation & Metrics

Figure 17 Definition of Edges: basin, escape, monotonic, crossovel Visualisation & Metrics

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UI bw IV VeYVVY 42vVUil. Nadarajen Veerapen is a Research Fellow at the University of Stirling in Scotland. He holds a PhD in Computer Science from the University of Angers, France. His research interests include local search, hybrid methods, search-based software engineering and visualisation. He has served as Student Affairs Chair for GECCO 2017 and GECCO 2018 and has co-organised the workshop on Landscape-Aware Heuristic Search at PPSN 2016 and GECCO 2017 and GECCO 2018.
UI bw IV VeYVVY 42vVUil. Nadarajen Veerapen is a Research Fellow at the University of Stirling in Scotland. He holds a PhD in Computer Science from the University of Angers, France. His research interests include local search, hybrid methods, search-based software engineering and visualisation. He has served as Student Affairs Chair for GECCO 2017 and GECCO 2018 and has co-organised the workshop on Landscape-Aware Heuristic Search at PPSN 2016 and GECCO 2017 and GECCO 2018.
By Thomas Splettstoesser (link) (www.scistyle.com) - Own work
By Thomas Splettstoesser (link) (www.scistyle.com) - Own work
2D function landscape (left), and a contour plot of the local optima partition of space into basins of attraction (right). A simple regular network of six local maxima can be observed
2D function landscape (left), and a contour plot of the local optima partition of space into basins of attraction (right). A simple regular network of six local maxima can be observed
w,, proportion of transitions from solutions s € Bi to solutions s’ € Bj
w,, proportion of transitions from solutions s € Bi to solutions s’ € Bj
What features of the fitness landscape are responsible for the widely different behaviours? Most fitness landscape metrics are insensitive/oblivious to the easy/hard phase transition!
What features of the fitness landscape are responsible for the widely different behaviours? Most fitness landscape metrics are insensitive/oblivious to the easy/hard phase transition!
DIMACS random instances
DIMACS random instances
DIMACS random instances
DIMACS random instances
2D layout and 3D projection where z coordinate is fitness
2D layout and 3D projection where z coordinate is fitness
«* It is not necessary to use Genetic Programming «* Other methods such a Genetic Algorithms may be usec «* Local Search is used in this case study
«* It is not necessary to use Genetic Programming «* Other methods such a Genetic Algorithms may be usec «* Local Search is used in this case study
«* Mutations of Boolean operators (&&, ||) ** Mutation operator: change one operator randoml “* Hill climber neighbourhood: change one operator ee Ranracantation: vector of intaqare
«* Mutations of Boolean operators (&&, ||) ** Mutation operator: change one operator randoml “* Hill climber neighbourhood: change one operator ee Ranracantation: vector of intaqare
(Langdon, Veerapen, Ochoa. EuroGP 2017’ Veerapen, Daolio, Ochoa. GECCO comp. 2017) 54
(Langdon, Veerapen, Ochoa. EuroGP 2017’ Veerapen, Daolio, Ochoa. GECCO comp. 2017) 54
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