On the importance of specialists for lexicase selection

Helmuth, Thomas; Pantridge, Edward; Spector, Lee

doi:10.1007/s10710-020-09377-2

Cited by 23 publications

(17 citation statements)

References 33 publications

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“…The disadvantage here is that the structural information of the training data is lost due to the compression to a single fitness value [43]. Contrary, with lexicase selection [44], [45], the information of the individual training cases is used. For the selection of a solution, the training cases are shuffled and every solution in the population is evaluated on the first one.…”

Section: A Stack-based Gpmentioning

confidence: 99%

“…Using PushGP, lexicase selection variants have been in recent work often compared to other selection methods (e.g., tournament selection) and achieved best success rates on many program synthesis benchmark problems [16], [29], [46], [47], [48], [49], [50], [51], [52], [53], [45].…”

Section: A Stack-based Gpmentioning

confidence: 99%

“…Replace Space with Newline [16], [29], [46], [82], [47], [74], [48], [39], [75], [36], [83], [50], [51], [81], [84], [15], [76], [52], [40], [42], [80], [45], [85], [54], [38], [77], [49] [12], [63], [54] -30…”

Section: Benchmark Problem Stack-based Gp Grammar-guided Gp Linear Gp...mentioning

confidence: 99%

“…String Lengths Backwards [16], [29], [46], [82], [47], [74], [48], [39], [75], [50], [81], [15], [76], [52], [40], [42], [80], [45], [38] [11], [86], [12], [2], [63] -24…”

Section: Benchmark Problem Stack-based Gp Grammar-guided Gp Linear Gp...mentioning

confidence: 99%

“…Last Index of Zero [16], [29], [74], [48], [39], [75], [50], [51], [76], [52], [40], [53], [42], [41], [80], [45], [38] [11], [61], [12], [2], [63], [72] [72] 24…”

Section: Benchmark Problem Stack-based Gp Grammar-guided Gp Linear Gp...mentioning

confidence: 99%

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Recent Developments in Program Synthesis with Evolutionary Algorithms

Sobania¹,

Schweim²,

Rothlauf³

2021

Preprint

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The automatic generation of computer programs is one of the main applications with practical relevance in the field of evolutionary computation. With program synthesis techniques not only software developers could be supported in their everyday work but even users without any programming knowledge could be empowered to automate repetitive tasks and implement their own new functionality. In recent years, many novel program synthesis approaches based on evolutionary algorithms have been proposed and evaluated on common benchmark problems. Therefore, we identify in this work the relevant evolutionary program synthesis approaches and provide an in-depth analysis of their performance. The most influential approaches we identify are stack-based, grammar-guided, as well as linear genetic programming. Further, we find that these approaches perform well on benchmark problems if there is a simple mapping from the given input to the correct output. On problems where this mapping is complex, e.g., if the problem consists of several subproblems or requires iteration/recursion for a correct solution, results tend to be worse. Consequently, for future work, we encourage researchers not only to use a program's output for assessing the quality of a solution but also the way towards a solution (e.g., correctly solved sub-problems).

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Section: A Stack-based Gpmentioning

confidence: 99%

Section: A Stack-based Gpmentioning

confidence: 99%

Section: Benchmark Problem Stack-based Gp Grammar-guided Gp Linear Gp...mentioning

confidence: 99%

“…String Lengths Backwards [16], [29], [46], [82], [47], [74], [48], [39], [75], [50], [81], [15], [76], [52], [40], [42], [80], [45], [38] [11], [86], [12], [2], [63] -24…”

Section: Benchmark Problem Stack-based Gp Grammar-guided Gp Linear Gp...mentioning

confidence: 99%

“…Last Index of Zero [16], [29], [74], [48], [39], [75], [50], [51], [76], [52], [40], [53], [42], [41], [80], [45], [38] [11], [61], [12], [2], [63], [72] [72] 24…”

Section: Benchmark Problem Stack-based Gp Grammar-guided Gp Linear Gp...mentioning

confidence: 99%

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