DecisionFocusedLearningBenchmarks.jl

[!WARNING] This package is currently under active development. The API may change in future releases.

DecisionFocusedLearningBenchmarks.jl provides a collection of benchmark problems for evaluating Decision-Focused Learning algorithms, spanning static, stochastic, and dynamic settings. Each benchmark provides a dataset generator, a statistical model architecture, and a combinatorial oracle, ready to plug into any DFL training algorithm:

using DecisionFocusedLearningBenchmarks

bench = ArgmaxBenchmark()
dataset = generate_dataset(bench, 100)
model = generate_statistical_model(bench)
maximizer = generate_maximizer(bench)

For the full list of benchmarks, the common interface, and detailed usage examples, refer to the documentation.

Related Packages

This package is part of the JuliaDecisionFocusedLearning organization, and built to be compatible with other packages in the ecosystem:

• InferOpt.jl: differentiable optimization layers and losses for decision-focused learning
• DecisionFocusedLearningAlgorithms.jl: collection of generic black-box implementations of decision-focused learning algorithms