Banks, D., Petralia, F., & Wang, S. (2011). Adversarial risk analysis: Borel games. Applied Stochastic Models in Business and Industry 27(2), pp. 72-86.10.1002/asmb.890
Brown, G. & Washburn, A.R. (2000 rev. 2004). The fast theater model (FATHM), Project Report, (NPS-OR-01-002-PR), Naval Postgraduate School, Monterey, CA.
Caswell, D. J., Howard, R. A., & Paté-Cornell, M. E. (2011). Analysis of national strategies to counter a country's nuclear weapons program. Decision Analysis, 8(1), 30-45.10.1287/deca.1110.0198
Davis, P. K., & Blumenthal, D. (1991). The base of sand problem: A white paper on the state of military combat modeling (No. RAND/N-3148-OSD/DARPA). Defense Advanced Research Projects Agency, Arlington VA.
Golany, B., Kaplan, E. H., Marmur, A., & Rothblum, U. G. (2009). Nature plays with dice-terrorists do not: Allocating resources to counter strategic versus probabilistic risks. European Journal of Operational Research, 192(1), 198-208.10.1016/j.ejor.2007.09.001
Kangas, L. (2005). Taistelun stokastinen mallinnus. Master's Thesis, Helsinki University of Technology. http://sal.aalto.fi/publications/pdf-files/tkan05.pdf Accessed: 2014-05-07
Kangas, L. & Lappi, E. (2006) Probabilistic risk analysis in combat modeling. In: Hämäläinen, J. (ed.) Lanchester and Beyond. A Workshop on Operational Analysis Methodology. PVTT Publications 11
Kangaspunta, J., Liesiö, J., & Salo, A. (2012). Cost-efficiency analysis of weapon system portfolios. European Journal of Operational Research, 223(1), pp. 264-275.10.1016/j.ejor.2012.05.042
Kovenock, D., Roberson, B. (2010). Conflicts with multiple battlefields, CESifo working paper: Empirical and Theoretical Methods, No. 316510.2139/ssrn.1679624
Kroshl, W. M., Sarkani, S., & Mazzuchi, T. A. (2015). Efficient allocation of resources for defense of spatially distributed networks using agent‐based simulation. Risk Analysis (to appear).10.1111/risa.12325
Lappi, E., Pakkanen, M., & Åkesson, B. (2012). An approximative method of simulating a duel. In: Proceedings of the Winter Simulation Conference, WSC '12, pp. 208:1-208:1010.1109/WSC.2012.6465044
Lappi, E., Pentti, J., Åkesson, B., Roponen, J., Valtonen, J., Koskinen, J., Burhan, U., Sivertun, Å., and Hämäläinen, J. (2015). Team 4: Data farm. manuscript.
Paté-Cornell, E., & Guikema, S. (2002). Probabilistic modeling of terrorist threats: A systems analysis approach to setting priorities among countermeasures. Military Operations Research, 7(4), pp. 5-23.10.5711/morj.7.4.5
Reese, W. (1980). Deception in a game theoretic framework. In: Daniel, D. C., Herbig, K. L., Reese, W., Heuer, R. J., & Sarbin, T. R. (1980). Multidisciplinary Perspectives on Military Deception (No. NPS-56-80-012A). Naval Postgraduate School, Monterey, CA.
Rios Insua, D., Rios, J., & Banks, D. (2009). Adversarial risk analysis. Journal of the American Statistical Association, 104(486), pp. 841-854.10.1198/jasa.2009.0155
Zhuang, J., & Bier, V. M. (2007). Balancing terrorism and natural disasters-defensive strategy with endogenous attacker effort. Operations Research, 55(5), pp. 976-99110.1287/opre.1070.0434
Zuckerman, I., Kraus, S., & Rosenschein, J. S. (2012). The adversarial activity model for bounded rational agents. Autonomous Agents and Multi-Agent Systems, 24(3), 374-409.10.1007/s10458-010-9153-2
Åkesson, A. (2012). Automatic calculation of win probabilities and conditional strength distribution of units in stochastic simulation model. Master's Thesis, Åbo Akademi University.