Terrain Representation And Reasoning In Computer Generated Forces : A Survey Of Computer Generated Forces Systems And How They Represent And Reason About Terrain

Report on a survey of computer systems used to produce realistic or intelligent behavior by autonomous entities in simulation systems. In particular, it is concerned with the data structures used by computer generated forces systems to represent terrain and the algorithmic approaches used by those systems to reason about terrain

State-of-the-art Assessment For Simulated Forces

Summary of the review of the state of the art in simulated forces conducted to support the research objectives of Research and Development for Intelligent Simulated Forces

Integrating realistic human group behaviors into a networked 3D virtual environment

Distributed Interactive Simulation DIS-Java-VRML Working Group. Includes supplementary material provided from the contents of a CD-Rom issued containing the work of all three Working Group members and all supplementary material, in compressed format.Virtual humans operating inside large-scale virtual environments (VE) are typically controlled as single entities. Coordination of group activity and movement is usually the responsibility of their real world human controllers. Georeferencing coordinate systems, single-precision versus double-precision number representation and network delay requirements make group operations difficult. Mounting multiple humans inside shared or single vehicles, (i.e. air-assault operations, mechanized infantry operations, or small boat/riverine operations) with high fidelity is often impossible. The approach taken in this thesis is to reengineer the DIS-Java-VRML Capture the Flag game geolocated at Fort Irwin, California to allow the inclusion of human entities. Human operators are given the capability of aggregating or mounting nonhuman entities for coordinated actions. Additionally, rapid content creation of human entities is addressed through the development of a native tag set for the Humanoid Animation (H-Anim) 1.1 Specification in Extensible 3D (X3D). Conventions are demonstrated for integrating the DIS-Java-VRML and H-Anim draft standards using either VRML97 or X3D encodings. The result of this work is an interface to aggregate and control articulated humans using an existing model with a standardized motion library in a networked virtual environment. Virtual human avatars can be mounted and unmounted from aggregation entities. Simple demonstration examples show coordinated tactical maneuver among multiple humans with and without vehicles. Live 3D visualization of animated humanoids on realistic terrain is then portrayed inside freely available web browsers.Approved for public release; distribution is unlimited

Exploring Fog of War Concepts in Wargame Scenarios

This thesis explores fog of war concepts through three submitted journal articles. The Department of Defense and U.S. Air Force are attempting to analyze war scenarios to aid the decision-making process; fog modeling improves realism in these wargame scenarios. The first article Navigating an Enemy Contested Area with a Parallel Search Algorithm [1] investigates a parallel algorithm\u27s speedup, compared to the sequential implementation, with varying map configurations in a tile-based wargame. The parallel speedup tends to exceed 50 but in certain situations. The sequential algorithm outperforms it depending on the configuration of enemy location and amount on the map. The second article Modeling Fog of War Effects in AFSIM [2] introduces the FAT for the AFSIM to introduce and manipulate fog in wargame scenarios. FAT integrates into AFSIM version 2.7.0 and scenario results verify the tool\u27s fog effects for positioning error, hits, and probability affect the success rate. The third article Applying Fog Analysis Tool to AFSIM Multi-Domain CLASS scenarios [3] furthers the verification of FAT to introduce fog across all war fighting domains using a set of CLASS scenarios. The success rate trends with fog impact for each domain scenario support FAT\u27s effectiveness in disrupting the decision-making process for multi-domain operations. The three articles demonstrate fog can affect search, tasking, and decision-making processes for various types of wargame scenarios. The capabilities introduced in this thesis support wargame analysts to improve decision-making in AFSIM military scenarios

Applications of agent architectures to decision support in distributed simulation and training systems

This work develops the approach and presents the results of a new model for applying intelligent agents to complex distributed interactive simulation for command and control. In the framework of tactical command, control communications, computers and intelligence (C4I), software agents provide a novel approach for efficient decision support and distributed interactive mission training. An agent-based architecture for decision support is designed, implemented and is applied in a distributed interactive simulation to significantly enhance the command and control training during simulated exercises. The architecture is based on monitoring, evaluation, and advice agents, which cooperate to provide alternatives to the dec ision-maker in a time and resource constrained environment. The architecture is implemented and tested within the context of an AWACS Weapons Director trainer tool. The foundation of the work required a wide range of preliminary research topics to be covered, including real-time systems, resource allocation, agent-based computing, decision support systems, and distributed interactive simulations. The major contribution of our work is the construction of a multi-agent architecture and its application to an operational decision support system for command and control interactive simulation. The architectural design for the multi-agent system was drafted in the first stage of the work. In the next stage rules of engagement, objective and cost functions were determined in the AWACS (Airforce command and control) decision support domain. Finally, the multi-agent architecture was implemented and evaluated inside a distributed interactive simulation test-bed for AWACS Vv\u27Ds. The evaluation process combined individual and team use of the decision support system to improve the performance results of WD trainees. The decision support system is designed and implemented a distributed architecture for performance-oriented management of software agents. The approach provides new agent interaction protocols and utilizes agent performance monitoring and remote synchronization mechanisms. This multi-agent architecture enables direct and indirect agent communication as well as dynamic hierarchical agent coordination. Inter-agent communications use predefined interfaces, protocols, and open channels with specified ontology and semantics. Services can be requested and responses with results received over such communication modes. Both traditional (functional) parameters and nonfunctional (e.g. QoS, deadline, etc.) requirements and captured in service requests

Topology-aware optimal task allocation framework for mission critical environment: Centralized and decentralized approaches

A Mission Critical Environment (MCE) consists of error-prone, highly variable, and highly rate limited communication channels. Paradoxically, this environment substantially increases the need to perform Optimal Task Allocation (OTA), while at the same time making it much harder to perform OTA efficiently. To perform OTA in MCE, in this thesis, I have proposed two novel automated algorithms. The first algorithm is called Centralized Optimal Task Allocation Algorithm (COTAA), where I consider OTA for publish/subscribe-based MCE since it has unique characteristics such as high level publish/subscribe node and task differentiation and high scalability. I also propose an architectural framework and communication protocols emphasizing the unique challenges of MCE. I adopt well known Hungarian Algorithm and Rectangular Assignment Algorithm to solve the OTA problem in polynomial time. The second algorithm is called Decentralized Optimal Task Allocation Algorithm (DOTAA) which exploits the concept of application-layer Distributed Hash Table (DHT) to perform OTA in MCE. Through simulations, I evaluate the performance of both COTAA and DOTAA for multiple mission critical scenarios. The results indicate that both COTAA and DOTAA achieve the goal of OTA in highly dynamic MCEs, with low processing time and communication overhead

BEHAVIORAL COMPOSITION FOR HETEROGENEOUS SWARMS

Research into swarm robotics has produced a robust library of swarm behaviors that excel at defined tasks such as flocking and area search, many of which have potential for application to a wide range of military problems. However, to be successfully applied to an operational environment, swarms must be flexible enough to achieve a wide array of specific objectives and usable enough to be configured and employed by lay operators. This research explored the use of the Mission-based Architecture for Swarm Composability (MASC) to develop mission-specific tactics as compositions of more general, reusable plays for use with the Advanced Robotic Systems Engineering Laboratory (ARSENL) swarm system. Three tactics were developed to conduct autonomous search of a geographic area and investigation of generated contacts of interest. The tactics were tested in live-flight and virtual environment experiments and compared to a preexisting monolithic behavior implementation completing the same task. Measures of performance were defined and observed that verified the effectiveness of solutions and confirmed the advantages that composition provides with respect to reusability and rapid development of increasingly complex behaviors.Lieutenant Commander, United States NavyApproved for public release. Distribution is unlimited

Autonomy of Military Robots: Assessing the Technical and Legal (“Jus In Bello”) Thresholds, 32 J. Marshall J. Info. Tech. & Privacy L. 57 (2016)

While robots are still absent from our homes, they have started to spread over battlefields. However, the military robots of today are mostly remotely controlled platforms, with no real autonomy. This paper will disclose the obstacles in implementing autonomy for such systems by answering a technical question: What level of autonomy is needed in military robots and how and when might it be achieved, followed by a techno-legal one: How to implement the rules of humanitarian law within autonomous fighting robots, in order to allow their legal deployment? The first chapter scrutinizes the significance of autonomy in robots and the metrics used to quantify it, which were developed by the US Department of Defense. The second chapter focuses on the autonomy of state-of-the-art” robots (e.g.; Google’s self-driving car, DARPA’s projects, etc.) for navigation, ISR or lethal missions. Based on public information, we will get a hint of the architectures, the functioning, the thresholds and technical limitations of such systems. The bottleneck to a higher autonomy of robots seems to be their poor “perceptive intelligence.” The last chapter looks to the requirements of humanitarian law (rules of “jus in bello”/rules of engagement) to the legal deployment of autonomous lethal robots on the battlefields. The legal and moral reasoning of human soldiers, complying with humanitarian law, is a complex cognitive process which must be emulated by autonomous robots that could make lethal decisions. However, autonomous completion of such “moral” tasks by artificial agents is much more challenging than the autonomous implementation of other tasks, such as navigation, ISR or kinetic attacks. Given the limits of current Artificial Intelligence, it is highly unlikely that robots will acquire such moral capabilities anytime soon. Therefore, for the time being, the autonomous weapon systems might be legally deployed, but only in very particular circumstances, where the requirements of humanitarian law happen to be irrelevant

Hybrid architectural framework for C4ISR and Discrete-Event Simulation (DES) to support sensor-driven model synthesis in real-world scenarios

While the application of a time-step approach in modeling C4ISR in Missile Defense Warfare (MDW) suffers inaccurate time estimation and relative slow speed, Discrete Event Simulation (DES) can elegantly satisfy these shortages. However, current DES frameworks typically rely on detailed efforts in event analysis for numerous replications before software modification of the simulation scenario can be meaningful. Such approaches have limited adaptability, especially regarding flexibility of scenario design and customizability of entity definition. This dissertation proposes an improved DES framework, Adjustable and Extensible Modeling Framework DES (AEMF-DES), which embeds the primary principles of a topical theme into a program to perform adjustable and extensible studies that can be explored by the analyst. To prove the feasibility of AEMF-DES, a Missile-Defense Simulation application (MDSIM) is also developed during this research. MSDIM simulates the C4ISR processes in Missile Defense Warfare and can estimate the overall effectiveness of a defenders deployment or attackers strategy. Additionally, based on the interest in sensor deployment evaluation, a k-coverage rate problem is also studied. Current k-coverage algorithms can only deal with binary and omnidirectional sensor models which cannot provide enough simulation fidelity if higher resolution is needed. An improved k-coverage rate algorithm is proposed in this research to handle the probabilistic and directional sensor models. A separate simulation test successfully demonstrates the feasibility of this new calculation algorithm in estimation of the k-coverage rate problem with probabilistic and directional sensor models. Considered together, the architecture implemented in this example software illustrates the value of integrating hybrid simulation techniques to support C4ISR analysis related to Missile Defense Warfare.http://archive.org/details/hybridrchitectur1094537598Lieutenant Commander, R.O.C. (Taiwan) NavyApproved for public release; distribution is unlimited

Optimizing combat capabilities by modeling combat as a complex adaptive system

Procuring combat systems in the Department of Defense is a balancing act where many variables, only some under control of the department, shift simultaneously. Technology changes non-linearly, providing new opportunities and new challenges to the existing and potential force. Money available changes year over year to fit into the overall US Government budget. Numbers of employees change through political demands rather than by cost-effectiveness considerations. The intent is to provide the best mix of equipment to field the best force against an expected enemy while maintaining adequate capability against the unexpected. Confounding this desire is the inability of current simulations to dynamically model changing capabilities and the very large universe of potential combinations of equipment and tactics.;The problem can be characterized as a stochastic, mixed-integer, non-linear optimization problem. This dissertation proposes to combine an agent-based model developed to test solutions that constitute both equipment capabilities and tactics with a co-evolutionary genetic algorithm to search this hyper-dimensional solution space. In the process, the dissertation develops the theoretical underpinning for using agent-based simulations to model combat. It also provides the theoretical basis for improvement of search effectiveness by co-evolving multiple systems simultaneously, which increases exploitation of good schemata and widens exploration of new schemata. Further, it demonstrates the effectiveness of using agent-based models and co-evolution in this application confirming the theoretical results.;An open research issue is the value of increased information in a system. This dissertation uses the combination of an agent-based model with a co-evolutionary genetic algorithm to explore the value added by increasing information in a system. The result was an increased number of fit solutions, rather than an increase in the fitness of the best solutions. Formerly unfit solutions were improved by increasing the information available making them competitive with the most fit solutions whereas already fit solutions were not improved