ibia-mar Scores
The results below are organized as follows:
- each table displays the solver’s performance for individual problem instances for the given task under different time limits
- table values are normalized scores for each evaluated problem as outlined in Evaluation Criteria
MAR
overall
Problem | 20sec | 1200sec | 3600sec |
---|---|---|---|
Alchemy_11 | 100.0 | 100.0 | 100.0 |
CSP_11 | 100.0 | 100.0 | 100.0 |
CSP_12 | 100.0 | 100.0 | 100.0 |
CSP_13 | 100.0 | 100.0 | 100.0 |
DBN_11 | 100.0 | 100.0 | 100.0 |
DBN_12 | 100.0 | 100.0 | 100.0 |
DBN_13 | 100.0 | 100.0 | 100.0 |
DBN_14 | 100.0 | 100.0 | 100.0 |
DBN_15 | 100.0 | 100.0 | 100.0 |
DBN_16 | 100.0 | 100.0 | 100.0 |
Grids_11 | 100.0 | 100.0 | 100.0 |
Grids_12 | 100.0 | 100.0 | 100.0 |
Grids_13 | 100.0 | 100.0 | 100.0 |
Grids_14 | 100.0 | 100.0 | 100.0 |
Grids_15 | 0.0 | 96.9 | 96.9 |
Grids_16 | 0.0 | 95.9 | 95.9 |
Grids_17 | 0.0 | 91.2 | 91.2 |
Grids_18 | 0.0 | 91.4 | 91.4 |
ObjectDetection_11 | 100.0 | 100.0 | 100.0 |
ObjectDetection_12 | 100.0 | 100.0 | 100.0 |
ObjectDetection_13 | 97.1 | 99.8 | 99.8 |
ObjectDetection_14 | 96.2 | 100.0 | 100.0 |
ObjectDetection_15 | 100.0 | 100.0 | 100.0 |
ObjectDetection_16 | 98.8 | 100.0 | 100.0 |
ObjectDetection_17 | 98.6 | 100.0 | 100.0 |
ObjectDetection_18 | 100.0 | 100.0 | 100.0 |
ObjectDetection_19 | 92.3 | 100.0 | 100.0 |
ObjectDetection_20 | 96.3 | 100.0 | 100.0 |
ObjectDetection_21 | 100.0 | 100.0 | 100.0 |
ObjectDetection_22 | 100.0 | 100.0 | 100.0 |
ObjectDetection_23 | 97.9 | 100.0 | 100.0 |
ObjectDetection_24 | 97.6 | 100.0 | 100.0 |
ObjectDetection_25 | 100.0 | 100.0 | 100.0 |
ObjectDetection_26 | 98.3 | 100.0 | 100.0 |
ObjectDetection_27 | 98.4 | 100.0 | 100.0 |
ObjectDetection_28 | 100.0 | 100.0 | 100.0 |
ObjectDetection_29 | 98.4 | 100.0 | 100.0 |
ObjectDetection_30 | 100.0 | 100.0 | 100.0 |
ObjectDetection_31 | 93.2 | 99.9 | 99.9 |
ObjectDetection_32 | 100.0 | 100.0 | 100.0 |
ObjectDetection_33 | 100.0 | 100.0 | 100.0 |
ObjectDetection_34 | 100.0 | 100.0 | 100.0 |
ObjectDetection_35 | 100.0 | 100.0 | 100.0 |
ObjectDetection_36 | 97.3 | 100.0 | 100.0 |
ObjectDetection_37 | 100.0 | 100.0 | 100.0 |
ObjectDetection_38 | 100.0 | 100.0 | 100.0 |
ObjectDetection_39 | 98.3 | 100.0 | 100.0 |
ObjectDetection_40 | 100.0 | 100.0 | 100.0 |
ObjectDetection_41 | 100.0 | 100.0 | 100.0 |
ObjectDetection_42 | 100.0 | 100.0 | 100.0 |
ObjectDetection_43 | 99.0 | 100.0 | 100.0 |
ObjectDetection_44 | 100.0 | 100.0 | 100.0 |
ObjectDetection_45 | 100.0 | 100.0 | 100.0 |
ObjectDetection_46 | 100.0 | 100.0 | 100.0 |
ObjectDetection_47 | 100.0 | 100.0 | 100.0 |
ObjectDetection_48 | 99.1 | 100.0 | 100.0 |
ObjectDetection_49 | 100.0 | 100.0 | 100.0 |
ObjectDetection_50 | 100.0 | 100.0 | 100.0 |
ObjectDetection_51 | 100.0 | 100.0 | 100.0 |
ObjectDetection_52 | 100.0 | 100.0 | 100.0 |
ObjectDetection_53 | 99.1 | 100.0 | 100.0 |
ObjectDetection_54 | 100.0 | 100.0 | 100.0 |
ObjectDetection_55 | 97.5 | 100.0 | 100.0 |
ObjectDetection_56 | 100.0 | 100.0 | 100.0 |
ObjectDetection_57 | 100.0 | 100.0 | 100.0 |
ObjectDetection_58 | 100.0 | 100.0 | 100.0 |
ObjectDetection_59 | 97.8 | 100.0 | 100.0 |
ObjectDetection_60 | 100.0 | 100.0 | 100.0 |
ObjectDetection_61 | 100.0 | 100.0 | 100.0 |
ObjectDetection_62 | 100.0 | 100.0 | 100.0 |
ObjectDetection_63 | 98.4 | 100.0 | 100.0 |
ObjectDetection_64 | 100.0 | 100.0 | 100.0 |
ObjectDetection_65 | 100.0 | 100.0 | 100.0 |
ObjectDetection_66 | 100.0 | 100.0 | 100.0 |
ObjectDetection_67 | 97.8 | 100.0 | 100.0 |
ObjectDetection_68 | 100.0 | 100.0 | 100.0 |
ObjectDetection_69 | 100.0 | 100.0 | 100.0 |
ObjectDetection_70 | 100.0 | 100.0 | 100.0 |
ObjectDetection_71 | 100.0 | 100.0 | 100.0 |
ObjectDetection_72 | 99.8 | 100.0 | 100.0 |
ObjectDetection_73 | 100.0 | 100.0 | 100.0 |
ObjectDetection_74 | 100.0 | 100.0 | 100.0 |
ObjectDetection_75 | 100.0 | 100.0 | 100.0 |
Pedigree_11 | 0.0 | 0.0 | 0.0 |
Pedigree_12 | 0.0 | 0.0 | 0.0 |
Pedigree_13 | 0.0 | 0.0 | 0.0 |
Promedus_11 | 0.0 | 0.0 | 0.0 |
Promedus_12 | 0.8 | 0.8 | 0.8 |
Promedus_13 | 0.0 | 0.0 | 0.0 |
Promedus_14 | 1.5 | 4.7 | 4.7 |
Promedus_15 | 6.3 | 6.3 | 6.3 |
Promedus_16 | 22.5 | 22.5 | 22.5 |
Promedus_17 | 0.0 | 0.0 | 0.0 |
Promedus_18 | 15.0 | 18.0 | 18.0 |
Promedus_19 | 0.0 | 33.6 | 33.6 |
Promedus_20 | 0.0 | 0.0 | 0.0 |
Promedus_21 | 5.8 | 5.8 | 5.8 |
Promedus_22 | 18.1 | 18.1 | 18.1 |
Promedus_23 | 6.0 | 6.0 | 6.0 |
Promedus_24 | 29.2 | 29.2 | 29.2 |
Promedus_25 | 16.0 | 16.0 | 16.0 |
Promedus_26 | 7.7 | 7.7 | 7.7 |
Promedus_27 | 2.2 | 2.2 | 2.2 |
Promedus_28 | 0.0 | 0.0 | 0.0 |
Promedus_29 | 17.1 | 17.1 | 17.1 |
Promedus_30 | 14.2 | 14.2 | 14.2 |
Promedus_31 | 5.1 | 5.1 | 5.1 |
Promedus_32 | 8.7 | 8.7 | 8.7 |
Promedus_33 | 10.7 | 10.7 | 10.7 |
Promedus_34 | 0.8 | 0.8 | 0.8 |
Promedus_35 | 1.2 | 1.2 | 1.2 |
Promedus_36 | 1.2 | 1.2 | 1.2 |
Promedus_37 | 4.3 | 4.3 | 4.3 |
Promedus_38 | 4.1 | 4.1 | 4.1 |
Segmentation_11 | 100.0 | 100.0 | 100.0 |
Segmentation_12 | 100.0 | 100.0 | 100.0 |
Segmentation_13 | 100.0 | 100.0 | 100.0 |
Segmentation_14 | 100.0 | 100.0 | 100.0 |
Segmentation_15 | 100.0 | 100.0 | 100.0 |
Segmentation_16 | 100.0 | 100.0 | 100.0 |
linkage_12 | 0.0 | 91.2 | 91.2 |
linkage_13 | 0.0 | 94.0 | 94.0 |
linkage_14 | 98.7 | 99.6 | 99.6 |