Bayesian Games for Threat Prediction and Situation Analysis

Higher levels of the JDL model call for prediction of future development and awareness of the development of a situation. Since the situations handled by Command and Control systems develop by actions performed by opposing agents, pure probabilistic or evidential techniques are not quite sufficient tools for prediction. Game theoretic tools can give an improved appreciation of the real uncertainty in this prediction task, and also be a tool in the planning process. We review recent developments in game theory and apply them in a decision support tool for Command and Control situation awareness enhancements.

[1]  Erik Durschmied.  The Hinge Factor: How Chance and Stupidity Have Changed History , 1999 .

[2]  B. Stengel,et al.  Efficient Computation of Behavior Strategies , 1996 .

[3]  Thomas P Coakley,et al.  Command and Control for War and Peace , 1992 .

[4]  Simon Ahlberg,et al.  The IFD03 Information Fusion Demonstrator , 2004 .

[5]  Klas Wallenius,et al.  Support for situation awareness in command and control , 2004 .

[6]  Dan Corey.  Intelligence Preparation of the Battlefield Needs Space , 2001 .

[7]  Richard W. Cottle,et al.  Linear Complementarity Problem. , 1992 .

[8]  Bernhard von Stengel,et al.  Fast algorithms for finding randomized strategies in game trees , 1994, STOC '94.

[9]  Ya'akov Gal,et al.  A language for modeling agents' decision making processes in games , 2003, AAMAS '03.

[10]  Gary E. Horne.  Maneuver warfare distillations: essence not verisimilitude , 1999, WSC '99.

[11]  Joel Brynielsson,et al.  Game Environment for Command and Control Operations (GECCO) System Description , 2001 .

[12]  J. Nash.  NON-COOPERATIVE GAMES , 1951, Classics in Game Theory.

[13]  Rina Azoulay-Schwartz,et al.  Negotiation on Data Allocation in Multi-Agent Environments , 1997, Autonomous Agents and Multi-Agent Systems.

[14]  Avi Pfeffer,et al.  Representations and Solutions for Game-Theoretic Problems , 1997, Artif. Intell..

[15]  F.E. White,et al.  Managing data fusion systems in joint and coalition warfare , 1999, Conference Record of the Thirty-Third Asilomar Conference on Signals, Systems, and Computers (Cat. No.CH37020).

[16]  Peter Thunholm,et al.  Military decision making and planning : towards a new prescriptive model , 2003 .

[17]  Berndt Brehmer,et al.  Using Microworlds To Study Intuitive Battle Dynamics: A Concept For The Future , 1999 .

[18]  S. Zamir,et al.  Formulation of Bayesian analysis for games with incomplete information , 1985 .

[19]  Alan N. Steinberg,et al.  Revisions to the JDL data fusion model , 1999, Defense, Security, and Sensing.

[20]  Robert Suzic,et al.  Representation and Recognition of Uncertain Enemy Policies Using Statistical Models , 2004 .

[21]  Eric Horvitz,et al.  The Lumière Project: Bayesian User Modeling for Inferring the Goals and Needs of Software Users , 1998, UAI.

[22]  Peter Norvig,et al.  Artificial Intelligence: A Modern Approach , 1995 .

[23]  Roger B. Myerson,et al.  Game theory - Analysis of Conflict , 1991 .

[24]  John C. Harsanyi,et al.  Games with Incomplete Information Played by "Bayesian" Players, I-III: Part I. The Basic Model& , 2004, Manag. Sci..

[25]  B. Butler,et al.  "Game Commander"-applying an architecture of game theory and tree lookahead to the command and control process , 1994, Fifth Annual Conference on AI, and Planning in High Autonomy Systems.

[26]  Stuart J. Russell,et al.  Dynamic bayesian networks: representation, inference and learning , 2002 .

[27]  Edmund H. Durfee,et al.  Rational Coordination in Multi-Agent Environments , 2000, Autonomous Agents and Multi-Agent Systems.

[28]  Ronnie Johansson,et al.  Information Acquisition in Data Fusion Systems , 2003 .

[29]  Daphne Koller,et al.  Multi-Agent Influence Diagrams for Representing and Solving Games , 2001, IJCAI.