Abstract
For managing the ever increasing variability of hardware/software interfaces (HSIs), e.g., in automotive systems, there is a need for the reuse of already existing HSIs. This reuse should be automated, and we (meta-)modeled the HSI domain for design space exploration. These models together with additionally defined transformation rules that lead from a model of one specific HSI to another one facilitate automatic adaptations of HSI instances in these models and, hence, both case-based reasoning (CBR) and (heuristic) search. Using these approaches for solving concrete problem instances, estimating their difficulty really matters, but there is not much theory available.
This work compares different approaches to estimating problem instance difficulty (similarity metrics, heuristic functions). It also shows that even measuring problem instance difficulty depends on the ground truth available and used. In order to avoid finding only domain-specific insights, we also employed sliding-tile puzzles for our experiments. The experimental results in both domains show how different approaches statistically correlate. Overall, this paper investigates problem instance difficulty for CBR and heuristic search. This investigation led to the insight that admissible functions guiding heuristic search may also be used for retrieving cases for CBR.
Roman Popp did this work when he was with the Institute of Computer Technology at TU Wien.
Thomas Rathfux did this work when he was with the Institute of Computer Technology at TU Wien.
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Abbreviations
- s, t:
-
Start node and goal node, respectively
- \(g^*(n)\) :
-
Cost of an optimal path from s to n
- \(h^*(n)\) :
-
Cost of an optimal path from n to t
- g(n), h(n):
-
Estimates of \(g^*(n)\) and \(h^*(n)\) , respectively
- f(n):
-
Static evaluation function: \(g(n) + h(n)\)
- \(C^*\) :
-
Cost of an optimal path from s to t
- \(N\#\) :
-
Number of nodes generated
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Acknowledgments
The InteReUse project (No. 855399) has been funded by the Austrian Federal Ministry of Transport, Innovation and Technology (BMVIT) under the program “ICT of the Future” between September 2016 and August 2019. More information can be found at https://iktderzukunft.at/en/.
The VIATRA team provided us with their VIATRA2 tool. Our implementations of the Fifteen Puzzle are based on the very efficient C code of IDA* and A* made available by Richard Korf and an efficient hashing schema by Jonathan Shaeffer. Ariel Felner and Shahaf Shperberg provided us with hints about the availability of code for the Fifteen Puzzle pattern databases.
Last but not least, Alexander Seiler and Lukas Schröer helped us with getting all the C code running under Windows for our Fifteen Puzzle experiment.
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Kaindl, H., Hoch, R., Popp, R., Rathfux, T., Lukasch, F. (2021). An Investigation of Problem Instance Difficulty for Case-Based Reasoning and Heuristic Search. In: Filipe, J., Śmiałek, M., Brodsky, A., Hammoudi, S. (eds) Enterprise Information Systems. ICEIS 2020. Lecture Notes in Business Information Processing, vol 417. Springer, Cham. https://doi.org/10.1007/978-3-030-75418-1_9
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