diff --git a/.idea/ActiveBOToytask.iml b/.idea/ActiveBOToytask.iml
index fa79220..09bfacf 100644
--- a/.idea/ActiveBOToytask.iml
+++ b/.idea/ActiveBOToytask.iml
@@ -4,7 +4,7 @@
-
+
diff --git a/.idea/misc.xml b/.idea/misc.xml
index 7e39aa8..dc9ea49 100644
--- a/.idea/misc.xml
+++ b/.idea/misc.xml
@@ -1,4 +1,4 @@
-
+
\ No newline at end of file
diff --git a/BoTorchTest/botorchtest1.py b/BoTorchTest/botorchtest1.py
new file mode 100644
index 0000000..4e10e9d
--- /dev/null
+++ b/BoTorchTest/botorchtest1.py
@@ -0,0 +1,26 @@
+import torch
+from botorch.models import SingleTaskGP
+from botorch.fit import fit_gpytorch_mll
+from botorch.utils import standardize
+from gpytorch.mlls import ExactMarginalLogLikelihood
+
+from botorch.acquisition import UpperConfidenceBound
+from botorch.optim import optimize_acqf
+
+
+train_X = torch.rand(10, 2, dtype=torch.double)
+Y = 1 - torch.norm(train_X - 0.5, dim=-1, keepdim=True)
+Y = Y + 0.1 * torch.randn_like(Y) # add some noise
+train_Y = standardize(Y)
+
+gp = SingleTaskGP(train_X, train_Y)
+mll = ExactMarginalLogLikelihood(gp.likelihood, gp)
+fit_gpytorch_mll(mll)
+
+UCB = UpperConfidenceBound(gp, beta=0.1)
+
+bounds = torch.stack([torch.zeros(2), torch.ones(2)])
+candidate, acq_value = optimize_acqf(
+ UCB, bounds=bounds, q=1, num_restarts=5, raw_samples=20,
+)
+print(candidate)
\ No newline at end of file
diff --git a/runner/BOGymRunner.py b/runner/BOGymRunner.py
index 94ff760..13733f3 100644
--- a/runner/BOGymRunner.py
+++ b/runner/BOGymRunner.py
@@ -5,10 +5,10 @@ import numpy as np
import matplotlib.pyplot as plt
# BO parameters
-env = Continuous_MountainCarEnv()
+env = Continuous_MountainCarEnv()
nr_steps = 100
acquisition_fun = 'ei'
-iteration_steps = 200
+iteration_steps = 100
nr_runs = 100