Military simulator a case study

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Military simulator


<ul><li> 1. Military Simulator- A Case Study Submitted by: Anubhav Singhal(10104774) Shruti Jadon(10104776) Abhinav Thakur(10104778) Project Supervisor: Mrs. Suma Dawn DEPARTMENT OF COMPUTER SCIENCE ENGINEERING &amp; INFORMATION TECHOLOGY JAYPEE INSTITUTE OF INFORMATION TECHNOLOGY, NOIDA </li> <li> 2. INTRODUCTION Military simulations, also known informally as war games, are simulations in which theories of warfare can be tested and refined without the need for actual hostilities and can be parameterized by numerous variables. Military simulations are seen as a useful way to develop tactical, strategy and doctrinal solutions approximate nature of the models used. </li> <li> 3. Problem Statement Designing of a military simulator to experiment the ground based search-and-rescue tactics behind the enemy lines using a game engine. The simulator will also be designed to train the soldiers in the tactics of search and rescue operations. The simulator will support multiplayer against Non player Characters. </li> <li> 4. Proposed solution The success of a tactic will be determined on the parameter of quantity of resources used &amp; number of soldiers killed during the execution of the mission. Tactic in which the number of soldiers left is maximum and number of killed allied soldiers is maximum is the most efficient tactic. If there is mixed result among different tactics, the number of soldiers left will be given priority as the main mission is saving our soldiers lives. This simulator is being designed on Unity which is currently one of the best free gaming engines available in the market. The Artificial Intelligence of the Non Player Characters will be designed Based on the papers It will designed to mimic the behavior of an enemy under the specific conditions which prevail in Search-and-Rescue operations. </li> <li> 5. Novelty/Benefits Currently there is no military simulator which is freely available to public. All simulators are currently available to military personals undergoing training. The public can not tweak or improve the simulators. These simulators do not take advantage of the FOSS community which may help in bringing a revolution in simulator as they did in the domain of operating systems and applications. This project tries to bridge this gap between the FOSS community and the simulators. In long term this help is creating a better human Artificial Intelligence within these simulators which can be used in other application like robotics. </li> <li> 6. Diagrammatic Summary of Literature Survey Figure : Back End model </li> <li> 7. Tools &amp; Framework used Unity 3D Unity is a game development ecosystem: a powerful rendering engine fully integrated with a complete set of intuitive tools and rapid workflows to create interactive 3D and 2D content; easy multiplatform publishing; thousands of quality, ready-made assets in the Asset Store and a knowledge-sharing community. </li> <li> 8. 3D max modeling- 3ds Max provides a number of different modeling toolsets and workflows, each with its positive and negative sides. These include Procedural Modeling (parametric objects and non-destructive modifiers), Editable Mesh and Editable Poly explicit modeling, Surface Tools Spline to Patch modeling and NURBS. Rain (AI)- RAIN has been specifically engineered to meet the demanding challenges of creating interactive characters. This means RAIN is intuitive, flexible, and powerful enough to handle an astonishing amount of complexity while offering cutting-edge behavior control. </li> <li> 9. Requirement Specifications </li> <li> 10. Overall architecture with component description &amp; dependency details TOOLS: Unreal Development Kit, 3DMax, Blender SUBJECT: Soldier, Gamer, Military Enthusiast, Military tactical scientist OBJECT: Experiment tactics, Train Soldiers COMMUNITY: Soldier, Gamer, Military Enthusiast, Military tactical Scientist, Game Developers RULES: Military tactical Scientist, Game Developers, Soldier, Game Engine DIVISION OF LABOUR: Soldier , Military tactical Scientist, Game Developers OUTCOME: Experiment tactics, Train Soldiers </li> <li> 11. Continued Subject: He is the person who will be using the system. Object: The objective of the subjects Outcome: The final outcome of using the system. Tools: The tools used to build the system. Rules: The people or system who will decide the rules based on which the system will work. Community: Any person who affects the system in any way or the system is affected by him. Division of Labor: People who develop the system. </li> <li> 12. Data Structures &amp; Algorithms Patrol Stop Patrol Around Sit Talk Look Around Decide path and follow it Figure: Algorithm Representation (Patrol) </li> <li> 13. Active Search Run towards the enemy Seek out enemy Select the pathway Figure: Algorithm Representation(Active Search) </li> <li> 14. Implementation Scenario </li> <li> 15. These are the variables on which Scenario depends. </li> <li> 16. Behavior tree </li> <li> 17. Random Forest Training Set </li> <li> 18. Random Forest Test Set </li> <li> 19. Simple cart Training Set </li> <li> 20. Simple cart Test set </li> <li> 21. Limitations of the solution As we are trying to make this simulator available for the FOSS community, we have to make this project on a free version of Unity 3D using free assets and add-ons. These add-ons and assets are bugged and not updated frequently. Hence the development process is slow and tedious. We are also limited by the hardware of the system. A game is very resource intensive software hence we cant put in huge amount of detailing without any performance degradation. </li> <li> 22. CONCLUSION The equations, normalizations constant and parameters used for equating utility scores and probabilities are still up for debate and varies between simulator to simulator or person to person. They have to be tested and tried to test their validity. We have proposed an AI approach for a military simulator which is a mix of behaviour tree and utility based AI architectures. Instead of being static, the probabilities are being calculated dynamically based on the situation. Also, with the help of data mining we could find different ways to one solution. </li> <li> 23. References 1. Arjen Beij, William van der Sterren, 2005, Killzones AI Dynamic procedural tacticshttp://www.cgf- . 2. John E. Laird and Michael van Lent, 2001, Human- Level AIs Killer Application Interactive Computer Games oi=;rep=rep1&amp;type pdf . 3. Kevin Dill, Lockheed Martin, 2011, A Game AI Approach to Autonomous Control of Virtual Characters. ceedings/Documents/11136_Paper.pdf </li> <li> 24. 4. Konstantin Mitgutsch, Matthew Wise, 2011, Subversive Game Design for Recursive Learning. 5. Owen Macindoe,Leslie Pack Kaelbling and Tomas Lozano-Perez, 2012, Assistant Agents for Sequential Planning Problems. /viewFile/5495/5774 6. Patrik O. Hoyer , 2004, Non-negative Matrix Factorization with Sparseness Constraints. df/NMFscweb.pdf </li> <li> 25. 7. Simon Egenfeldt, Jonas Heide, 2003, Playing with fire How do computer games affect the player. pdf Song Wang, 2012, Operations Research 3OR. R/Notes.pdf 8. TANYA KHOVANOVA1 AND ZIV SCULLY2, 2013, EFFICIENT CALCULATION OF DETERMINANTS OF SYMBOLIC MATRICES WITH MANY VARIABLES. 9. Tony Manninen, 2001,Virtual Team Interactions in Networked Multimedia Games Case: Counter-Strike Multi-player 3D Action Game. 1.19.6314&amp;rep=rep1&amp;type=pdf </li> <li> 26. 10. Tony Manninen, 2001,Virtual Team Interactions in Networked Multimedia Games Case: Counter-Strike Multi-player 3D Action Game. 1.19.6314&amp;rep=rep1&amp;type=pdf 11. William van der Sterren, 2001, Terrain Reasoning for 3D Action Games. http://www.cgf- 12. Using CmapTools to Construct Activity System systems/ </li> </ul>


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