A Preliminary Counterfactual Explanation Method for Genetic Programming-Evolved Rules: A Case Study on Uncertain Capacitated Arc Routing Problem
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- @InProceedings{wang:2024:GECCOcomp6,
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author = "Shaolin Wang and Yi Mei and Mengjie Zhang",
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title = "A Preliminary Counterfactual Explanation Method for
Genetic {Programming-Evolved} Rules: A Case Study on
Uncertain Capacitated Arc Routing Problem",
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booktitle = "Proceedings of the 2024 Genetic and Evolutionary
Computation Conference Companion",
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year = "2024",
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editor = "Ting Hu and Aniko Ekart",
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pages = "547--550",
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address = "Melbourne, Australia",
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series = "GECCO '24",
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month = "14-18 " # jul,
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organisation = "SIGEVO",
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publisher = "Association for Computing Machinery",
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publisher_address = "New York, NY, USA",
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keywords = "genetic algorithms, genetic programming,
hyper-heuristic, uncertain capacitated arc routing
problem, counterfactual explanation: Poster",
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isbn13 = "979-8-4007-0495-6",
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DOI = "doi:10.1145/3638530.3654192",
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size = "4 pages",
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abstract = "In this study, we propose a novel method to enhance
the interpretability of Genetic Programming
Hyper-Heuristics (GPHH) by employing counterfactual
explanations for Genetic Programming (GP) evolved rules
in dynamic stochastic combinatorial optimisation
problems. Focusing on GP-evolved rules, such as
dispatching and routing policies, our research tackles
the challenge of their complexity and improves user
understanding. We illustrate our methodology using the
Uncertain Capacitated Arc Routing Problem (UCARP) as a
case study. The approach involves analyzing potential
candidates in a scenario to understand why some are not
selected. We introduce metrics to evaluate the quality
of counterfactual explanations and adapt optimization
methods to produce them. Additionally, we present a new
attribute importance method based on these
explanations. This research contributes to enhancing
the transparency of GPHH in UCARP and may provide a
reference point for future investigations into
evolutionary computation and decision-making systems.",
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notes = "GECCO-2024 GP A Recombination of the 33rd
International Conference on Genetic Algorithms (ICGA)
and the 29th Annual Genetic Programming Conference
(GP)",
- }
Genetic Programming entries for
Shaolin Wang
Yi Mei
Mengjie Zhang
Citations