Scenario elicitation

G.Tecuci, Learning Agents Laboratory

Scenario elicitation

Scenario elicitation modules

Execution of the elicitation scripts

Sample elicitation scripts

Script editor

G.Tecuci, Learning Agents Laboratory

Scenario elicitation: hands-on experience

ScenarioElicitation

G.Tecuci, Learning Agents Laboratory

G.Tecuci, Learning Agents Laboratory

G.Tecuci, Learning Agents Laboratory

G.Tecuci, Learning Agents Laboratory

G.Tecuci, Learning Agents Laboratory

G.Tecuci, Learning Agents Laboratory

subconcept_of

<object>

Scenario

Script type: Elicit properties of an instance <scenario-name> of Scenario:Script calls:

Elicit the feature brief_description for <scenario-name>Elicit the feature description for <scenario-name>Elicit the feature has_as_opposing_force for <scenario-name>

elicitation_script

Script type: Elicit instances of ScenarioControls:

Question: “Provide a name for the scenario to be analyzed:”Answer variable: <scenario-name>Default value: “new-scenario”Control type: single-line

Ontology actions:<scenario-name> instance-of Scenario

Script calls:Elicit the properties of the instance <scenario-name>

elicitation_script

Sample elicitation scripts

G.Tecuci, Learning Agents Laboratory

subfeature_of

<feature>

Has_as_opposing_force

elicitation_script

Script type: Elicit the feature Has_as_opposing_force for an instance <scenario-name>

Controls:Question: Name the opposing forces in <scenario-name>Answer variable: <opposing-force>Control type: multiple-line, height 4

Ontology actions:<opposing-force> instance-of Opposing_force<scenario-name> Has_as_opposing_force <opposing-force>

Script calls:Elicit properties of the instance <opposing-force> in new window

Sample elicitation scripts (cont.)

G.Tecuci, Learning Agents Laboratory

<object>

Scenario

Force

Opposing_force

subconcept-of

subconcept-of

subconcept-of

instance-of

Sicily_1943 Anglo_allies_1943Has_as_opposing_force

instance-of

European_Axis_1943Has_as_opposing_force

instance-of

Script type: Elicit the feature Has_as_opposing_force for an instance <scenario-name>

Controls:Question: Name the opposing forces in <scenario-name>Answer variable: <opposing-force>Control type: multiple-line, height 4

Ontology actions:<opposing-force> instance-of Opposing_force<scenario-name> Has_as_opposing_force <opposing-force>

Script calls:Elicit properties of the instance <opposing-force> in new window

…

Execution of the elicitation scripts

G.Tecuci, Learning Agents Laboratory

Script editor: hands-on experience

ScriptEditor

G.Tecuci, Learning Agents Laboratory

G.Tecuci, Learning Agents Laboratory

G.Tecuci, Learning Agents Laboratory

G.Tecuci, Learning Agents Laboratory

G.Tecuci, Learning Agents Laboratory

G.Tecuci, Learning Agents Laboratory

G.Tecuci, Learning Agents Laboratory

G.Tecuci, Learning Agents Laboratory

G.Tecuci, Learning Agents Laboratory

G.Tecuci, Learning Agents Laboratory

G.Tecuci, Learning Agents Laboratory

G.Tecuci, Learning Agents Laboratory

G.Tecuci, Learning Agents Laboratory

G.Tecuci, Learning Agents Laboratory

Recommended reading

License, Learning Agents Laboratory, George Mason University, October 2001. (required)

Disciple-RKF/COG: Demo Guide, Learning Agents Laboratory, George Mason University, October 2001.

Installation,General Functions,Scenario Elicitation,Script Editor,Learning Agents Laboratory, George Mason University, October 2001.

Michael Bowman, Sicily COG Report, US Army War College, Spring 2001.