Improve Hartmann benchmark

Author: AVHopp

benchmarks/domains/__init__.py

@@ -28,7 +28,7 @@
 from benchmarks.domains.transfer_learning.easom.easom_tl_47_negate_noise5 import (
     easom_tl_47_negate_noise5_benchmark,
 )
-from benchmarks.domains.transfer_learning.hartmann.hartmann_tl_3_15_15 import (
+from benchmarks.domains.transfer_learning.hartmann.hartmann_tl_3_20_15 import (
     hartmann_tl_3_15_15_benchmark,
 )
 from benchmarks.domains.transfer_learning.michalewicz.michalewicz_tl_continuous import (

benchmarks/domains/transfer_learning/hartmann/hartmann_tl_3_15_15.py renamed to benchmarks/domains/transfer_learning/hartmann/hartmann_tl_3_20_15.py

@@ -28,7 +28,7 @@ def hartmann_tl_3_15_15(settings: ConvergenceBenchmarkSettings) -> pd.DataFrame:
     • Compares two versions of Hartmann function:
       - Target: standard Hartmann
       - Source: Hartmann with added noise (noise_std=0.15)
-    • Uses 15 points per dimension
+    • Uses 20 points per dimension
     • Tests transfer learning with different source data percentages:
       - 1% of source data
       - 10% of source data
@@ -43,8 +43,8 @@ def hartmann_tl_3_15_15(settings: ConvergenceBenchmarkSettings) -> pd.DataFrame:
     target_function = Hartmann(dim=3)
     source_function = Hartmann(dim=3, noise_std=0.15)
 
-    points_per_dim = 15
-    percentages = [0.01, 0.1, 0.2]
+    points_per_dim = 20
+    percentages = [0.01, 0.05, 0.1]
 
     # Create grid locations for the parameters
     bounds = np.array([[0.0, 0.0, 0.0], [1.0, 1.0, 1.0]])