feat: add initial tutorial3 for actions/effects feature

tutorials/tutorial3/actions_effects_lang.mal

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+// vim:ft=mal
+#id: "test-actions-effects"
+#version: "0.0.0"
+
+category System{
+
+    asset Computer {
+      & physicalAccess
+        -> attemptAuthenticate
+
+      | attemptAuthenticate [HardAndCertain]
+        -> authenticate
+
+      & effect authenticate
+        -> computerApps.attemptExploit
+    }
+
+    asset Application {
+      # shutDown
+        -> exploit
+
+      | attemptExploit [HardAndCertain]
+        -> exploit
+
+      & effect exploit
+        -> toApplications.attemptExploit,
+           dataOnApp.read
+    }
+
+    asset Data {
+      | read
+    }
+
+}
+
+associations {
+  Computer [computerOfApp] * <-- appExecution --> * [computerApps] Application
+  Application [fromApplications] * <-- AppToAppCommunication --> * [toApplications] Application
+  Data [dataOnApp] * <-- AppData --> * [appWithData] Application
+}

tutorials/tutorial3/tutorial3.md

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+## Tutorial 3 - actions and effects
+
+- Read through the language: actions_effects_lang.mal
+
+- Read through the scenario file
+
+
+Run the simulation with cli: `malsim tutorial3_scenario.yml`
+
+Run the simulation with cli and TTCMode = expected_value: `malsim tutorial3_scenario.yml --ttc-mode 3`
+
+Run the simulation with script: `python tutorial3.py`
+
+
+TODO: make this into an actual tutorial walking through each step of the process (creating the MAL language, using the MAL gui, writing the script).

tutorials/tutorial3/tutorial3.py

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+from maltoolbox.visualization import render_attack_graph, render_model
+from malsim import Scenario, MalSimulator, run_simulation, MalSimulatorSettings
+from malsim.config import TTCMode
+
+def main():
+    scenario_file = "tutorial3_scenario.yml"
+    scenario = Scenario.load_from_file(scenario_file)
+    simulator = MalSimulator.from_scenario(
+        scenario,
+        sim_settings=MalSimulatorSettings(
+            ttc_mode=TTCMode.EXPECTED_VALUE,
+            # attack_surface_skip_unnecessary=False
+        )
+    )
+    run_simulation(simulator, scenario.agent_settings)
+    render_attack_graph(scenario.attack_graph)
+    render_model(scenario.model)
+    import pprint
+    pprint.pprint(simulator.recording)
+
+
+if __name__ == '__main__':
+    main()

tutorials/tutorial3/tutorial3_scenario.yml

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+lang_file: /home/joakim-loxdal/Documents/mal-toolbox-tutorial/tutorials/tutorial3/actions_effects_lang.mal
+agents:
+  Attacker:
+    name: Attacker
+    type: attacker
+    entry_points: !!set
+      ComputerA:physicalAccess: null
+    goals: !!set
+      DataOnAppB:read: null
+    policy: RandomAgent
+model:
+  metadata:
+    name: actions_effects_model
+    langVersion: 0.0.0
+    langID: test-actions-effects
+    malVersion: 0.1.0-SNAPSHOT
+    MAL-Toolbox Version: 2.0.0
+    info: Created by the mal-toolbox model python module.
+  assets:
+    0:
+      name: ComputerA
+      type: Computer
+      associated_assets:
+        computerApps:
+          2: AppA
+      extras:
+        position:
+          x: -498.0
+          y: -247.0
+    2:
+      name: AppA
+      type: Application
+      associated_assets:
+        computerOfApp:
+          0: ComputerA
+        toApplications:
+          3: AppB
+        fromApplications:
+          3: AppB
+      extras:
+        position:
+          x: -495.0
+          y: -427.0
+    3:
+      name: AppB
+      type: Application
+      associated_assets:
+        fromApplications:
+          2: AppA
+        dataOnApp:
+          4: DataOnAppB
+        toApplications:
+          2: AppA
+      extras:
+        position:
+          x: -495.0
+          y: -618.0
+    4:
+      name: DataOnAppB
+      type: Data
+      associated_assets:
+        appWithData:
+          3: AppB
+      extras:
+        position:
+          x: 56.0
+          y: -616.0