Merge pull request #29 from convince-project:fix/link_active-plan-sim…

…ulate-plan

Fix/link_active-plan-simulate-plan

docs/source/index.rst

@@ -28,7 +28,7 @@ For a list of available software modules in the current release of the SIT-AW pi
 
 
 sit-l
-------
+-----
 SIT-L is a software module that implements techniques for the acquisition (learning) of new episodic and semantic memory from encountered unexpected situations that were not foreseen at design time (unknown anomalies). It closes the loop of robot situation awareness and increased robot autonomy. SIT-L is under development and will be release at a later stage of CONVINCE.
 
 SIT-L represents the extraction of the new anomaly description, given the preprocessed sensory-data, monitor outputs, ontologies and from the found solution to resolve the anomaly, i.e., the output of `ACTIVE-PLAN/SIMULATE-PLAN <https://convince-project.github.io/overview/#active-plan-simulate-plan>`_. A new pair (anomaly description, mitigation strategy) is then added to the current knowledge base, which implies learning a new situation. Indeed, if the system encounters this situation again, it will be able to identify the anomaly as known and resolve it.
@@ -83,7 +83,8 @@ This policy is then converted back to a BT using `existing methods <https://ieee
 REFINE-PLAN can be found `here <https://github.com/convince-project/refine-plan>`__ and its documentation can be found `here <https://convince-project.github.io/refine-plan>`__.
 The documentation contains a tutorial demonstrating the current functionality.
 
-active-plan & simulate-plan
+
+active-plan and simulate-plan
 -----------------------------
 ACTIVE-PLAN and SIMULATE-PLAN are tools used for handling unknown anomalies.
 These tools are currently being developed.
@@ -93,6 +94,7 @@ Anomalies are detected using `SIT-AW <https:///github.com/convince-project/sit-a
 `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. 
 
+
 scan
 ----
 `convince-project/scan <https:///github.com/convince-project/scan>`_
@@ -119,6 +121,7 @@ specific property by SCAN will only depend on the computation time
 allowed, whereas if probabilities are attached to transitions in the
 model, this will also influence the final result emitted by SCAN. 
 
+
 moon
 ----
 `convince-project/moon <https:///github.com/convince-project/moon>`_
@@ -136,6 +139,7 @@ SCAN. MOON will notify violations of properties and models so that
 other tools can be invoked to amend plans or models and adapt the
 control architecture to new and unforeseen situations. 
 
+
 mc-toolchain-jani
 -----------------
 `convince-project/mc-toolchain-jani <https:///github.com/convince-project/mc-toolchain-jani>`_
@@ -145,6 +149,7 @@ This is a toolbox for converting all specifications of components of a robotic s
 The toolbox consist of a script to convert models describing the system and its environment together, given in the CONVINCE robotics JANI flavor as specified in the `data model repository <https://github.com/convince-project/data-model>`_, into `plain JANI <https://jani-spec.org>`_ accepted as input by model checkers. 
 The second part of the toolbox centers around system specifications given in (SC)XML and how to convert them into a plain JANI file for model checking. This comprises property specification in temporal logic, currently given in JANI, a behavior tree in XML, ROS nodes and their plugins in SCXML, and an environment specification in SCXML.
 
+
 model2code
 ----------
 `convince-project/model2code <https:///github.com/convince-project/model2code>`_

docs/source/overview.plantuml

@@ -42,7 +42,7 @@ agent sitaw #LightGreen [
 WP2 / CEA
 
 ----
-[[https://convince-project.github.io/overview/#sit-l SIT-L]]
+[[https://convince-project.github.io/overview/#id1 SIT-L]]
 ....
 WP2 / CEA
 ]
@@ -66,12 +66,12 @@ agent coverageplan #PaleGreen [
 WP3 / UoB
 ]
 agent activeplan #PaleGreen [
-[[https://convince-project.github.io/overview/#active-plan-simulate-plan ACTIVE-PLAN]]
+[[https://convince-project.github.io/overview/#active-plan-and-simulate-plan ACTIVE-PLAN]]
 ....
 WP3 / UoB
 ] 
 agent simulateplan #PaleGreen [
-[[https://convince-project.github.io/overview/#active-plan-simulate-plan SIMULATE-PLAN]]
+[[https://convince-project.github.io/overview/#active-plan-and-simulate-plan SIMULATE-PLAN]]
 ....
 WP3 / UoB
 ]