International Data Farming Workshop 20 Group 17 Naval Postgraduate School 25 March 2010

Purpose and Agenda 1/27/20162 To discuss Strategic Data Farming (SDF) and utilize this technique to augment or enhance data farming (DF) in support of simulation analysis. Agenda Group 17 Members. Background. SDF Exemplar and Applicability. SDF and DF – Mutually Enhancing. Use Case and Analysis. Conclusions/Future Work. International Data Farming Workshop 20

Group 17 Members Dr. Deborah Duong – Augustine Consulting, Inc., Group Lead Dr. Johan Schubert – Deputy Research Director, Division for Information Systems, Swedish Defence Research Agency Ms. Mary McDonald – SEED Research Associate CPT Richard F. Brown – Operations Research Analyst, TRAC-MTRY 1/27/20163 International Data Farming Workshop 20

Background SDF is the use of combinatorial game theory to optimize player moves in wargames, scripted simulations, and agent based simulations, according to player’s goals. Players become automated agents that look ahead to results of moves assuming players are trying to achieve goals, in a simple, general cognitive model. Uses “Game Trees”, a common Artificial Intelligence technique. 1/27/20164 International Data Farming Workshop 20

SDF Exemplar 1/27/20165 Blue Red Blue {260, 250, 210, 300, 190} Blue player execution of SDF. Calculate “best” move by expanding the tree forward through the duration of the simulation using CONOPS and evaluating through evaluation functions/criteria. CONOPS do not have to be precise, as tree pruning will still add value/efficiency. –asd {120, 180, 150, 175, 140} {90, 170, 145, 160, 130} {90, 110, 100, 115, 120} {120, 100, 150, 175, 180} {185, 130, 155, 180, 100} Actual Simulation Run. Blue Cognition during game. International Data Farming Workshop 20

Applicability of SDF Validation, Verification, and Accreditation. SDF reveals how players can “game the game”. Concept of Operations (CONOPS) testing, to including Goals, Subgoals, Indicators, Decision Points, Branches and Sequels, Doctrine and Commander’s Guidance. –Traditional Data Farming comes up short because scripts are not reactive to the population or to the opponent. Information Operations (IO) Modeling. Modeling the opponents goals and perception is necessary for deception. 1/27/20166 International Data Farming Workshop 20

How DF enhances SDF DF can reveal how the performance of SDF depends on inputs such as: –initial conditions. –CONOPS (goals, threshold values). Can test different CONOPS, for example: 1/27/20167 SDF “Best” Next Moves Sequence of Actions Input Conditions Goals Threshold Values DF DOE Output International Data Farming Workshop 20

How SDF enhances DF SDF may help define the experimental region for DF –CONOPS is used to prune the “all possible branches” tree -May help to select/eliminate factors for further study -May help to define the feasibility region. –For real world problems, seems likely to reduce the experimental region by orders of magnitude. 1/27/20168 Red-SuicideBomber-Freq International Data Farming Workshop 20

SDF Use Case: OSD Analytical Baseline, Africa 1/27/20169 Green Goals Separate Tribe J from the insurgency. Improve Tribe J sentiment toward green. Red Goals Improve Tribe J sentiment toward insurgency. Separate Tribe J from green Green Move 1.Disrupt alliance between tribe J and tribe D. 2.Conduct Civil Affairs. Red Move 3.Make tribe O, a green ally, appear to harm tribe J. 4.Make green appear to harm tribe J. 5.Conduct stability operations. International Data Farming Workshop 20 SDF helps narrow the state space, sometimes substantially: N is the depth of the tree For this case, SDF reduces approximately 98% of the “feasible region.”

1/27/ Start International Data Farming Workshop 20 Green Action Red Reaction SDF Use Case: OSD Analytical Baseline, Africa G: 0.57 R: 1.0 GE: ((1-R)+G)/2 = 0.28 RE: 1-GE = 0.72 GE:.5 GE:.35 GE:.5 GE:.25 RE:.35RE:.65 RE:.75 RE:.5 1.Disrupt alliance between tribe J and tribe D. 2.Conduct Civil Affairs. 3.Make tribe O, a green ally, appear to harm tribe J. 4.Make green appear to harm tribe J. G and R are Popular Support Levels for Green and Red and GE and RE are Green Evaluation Function and Red Evaluation Function of the Levels. Each Side chooses to maximize their Evaluation Functions. Without looking ahead, Green’s choices seem the same (both are.5). But by looking ahead to how Red would react, he finds action Disruption (action 1) (GE=1-.65=.35) is better than CA (action 2) (GE=1-.75=.25)

Conclusions / Future Work Strategic Data Farming and analytical data farming can have a mutually supporting relationship. –Strategic data farming can add additional efficiency to analytical data farming. –Analytical data farming can make a strategic data farming approach more robust. Additional enhancement of Cultural Geography Model, resident at TRAC-MTRY, to allow for employment SDF technique. Application of SDF for TRAC Irregular Warfare Tactical Wargame. Strategic Data Farming article for academic journal. 1/27/ International Data Farming Workshop 20