Scenario elicitation modules Scenario elicitation Sample elicitation scripts

Scenario elicitation modules Scenario elicitation Sample elicitation scripts Execution of the elicitation scripts Script editor G. Tecuci, Learning Agents Laboratory

Scenario elicitation: hands-on experience Scenario Elicitation 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

Sample elicitation scripts <object> subconcept_of Scenario elicitation_script G. Tecuci, Learning Agents Laboratory Script type: Elicit instances of Scenario Controls: 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> Script type: Elicit properties of an instance <scenario-name> of Scenario: Script calls: Elicit the feature brief_description for <scenario-name> Elicit the feature has_as_opposing_force for <scenario-name>

Sample elicitation scripts (cont. ) <feature> subfeature_of Has_as_opposing_force elicitation_script G. Tecuci, Learning Agents Laboratory 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 <object> Script type: Elicit the feature Has_as_opposing_force subconcept-of for an instance <scenario-name> Controls: subconcept-of Force Question: Name the opposing forces in <scenario-name> Answer variable: <opposing-force> subconcept-of Scenario Control type: multiple-line, height 4 Ontology actions: Opposing_force <opposing-force> instance-of Opposing_force instance-of <scenario-name> Has_as_opposing_force <opposing-force> instance-of Script calls: Has_as_opposing_force Elicit properties of the instance <opposing-force> Anglo_allies_1943 instance-of Sicily_1943 in new window Has_as_opposing_force European_Axis_1943 … G. Tecuci, Learning Agents Laboratory

Script editor: hands-on experience Script Editor 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. G. Tecuci, Learning Agents Laboratory