Scenario elicitation
description
Transcript of 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.