What question did this study set out to answer?

The aim is to present supplementary data demonstrating the efficacy of operator-counting heuristics in dynamic programming.

April 15, 2026Open Access

Code, benchmarks, experiment data, and additional results for the ICAPS 2026 paper "Operator-Counting Heuristics for Domain-Independent Dynamic Programming"

Key Points

The aim is to present supplementary data demonstrating the efficacy of operator-counting heuristics in dynamic programming.
Provided supplementary PDF with detailed results and technical definitions
Included source code for implementation
Supplied benchmarks for four problem classes: BPP, m-PDTSP, TSP, Talent Scheduling
Shared experiment run logs and scripts for reproducibility
Detailed results are included in the supplementary PDF file
Benchmarks for diverse problems demonstrate the effectiveness of heuristics
Source code allows for replication of results and further experimentation

Abstract

Code, benchmarks, experiment data, and additional results for the ICAPS 2026 paper "Operator-Counting Heuristics for Domain-Independent Dynamic Programming" It contains: `supplementary.pdf`: a PDF containing detailed results explaining the findings, technical details of the DIDP definition and the translation to SMT `didp-rs-abstract-interpretation.zip`: source code (see README for build instructions) `benchmarks.zip`: DIDP models for the four problem classses: BPP, m-PDTSP, TSP, Talent Scheduling with instance `experiment-data.zip`: experiment run logs and scripts

Code, benchmarks, experiment data, and additional results for the ICAPS 2026 paper "Operator-Counting Heuristics for Domain-Independent Dynamic Programming"

Key Points

Abstract

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