Merge pull request #22 from convince-project/minor-fix

minor fix

docs/source/index.rst

@@ -91,7 +91,7 @@ The input here is an anomalous state where the robot failed to perform an action
 Anomalies are detected using `SIT-AW <https:///github.com/convince-project/sit-aw>`__.
 `Explainable AI planning <https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9635890>`__ is used to generate explanations about our systems, and these explanations will guide the robot to understand what went wrong and which actions need to be applied to reach an anomaly-free state.
 `Failure Mode and Effects Analysis <https://iopscience.iop.org/article/10.1088/1757-899X/337/1/012033/pdf>`__ is used to store the unknown anomalies we have encountered, once we have recovered.
- This is fed into a Bayesian Network to calculate the Conditional Probability Tables using `PyAgrum <https://pypi.org/project/pyAgrum/>`__ to infer which solution SIMULATE-PLAN can use to resolve the anomalies. 
+This is fed into a Bayesian Network to calculate the Conditional Probability Tables using `PyAgrum <https://pypi.org/project/pyAgrum/>`__ to infer which solution SIMULATE-PLAN can use to resolve the anomalies. 
 
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