| View Larger Image | Modeling Robot Swarms Using Agent-Based Simulation | Spiral-boundby Alistair Dickie (Author)
| 2 New starting at: | $31.95 |
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| | Binding: | Spiral-bound | | Publisher: | Storming Media | | Page Count: | 131 Pages | | Publication Date: | 2002 | | Sales Rank: | 3,433,872rd |
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Product Description
This is a NAVAL POSTGRADUATE SCHOOL MONTEREY CA report procured by the Pentagon and made available for public release. It has been reproduced in the best form available to the Pentagon. It is not spiral-bound, but rather assembled with Velobinding in a soft, white linen cover. The Storming Media report number is A018504. The abstract provided by the Pentagon follows: In the near future advances in mechanical and electrical engineering will enable the production of a wide variety of relatively low cost robotic vehicles. This thesis investigates the behavior of swans of military robots acting autonomously. The Multi-Agent Robot Swarm Simulation (MARSS) was developed for modeling the behavior of swarm of military robots. MARSS contains state, sensing, and behavioral model building tools that allow a range of complex entities and interactions to be represented. It is a model-building tool that draws theory and ideas from agent-based simulation, discrete event simulation, traditional operations research, search theory, swarm theory, and experimental design. MARS S enables analysts to explore the effect of individual behavioral factors on swarm performance. The performance response surface can be explored using designed experiments. A model was developed in MARS S to investigate the effects of increasing behavioral complexity for a search scenario involving a swarm of Micro Air Vehicles (MAV's) searching for mobile tanks in a region. Agreement between theoretical and simulated search scenarios for simple searchers was found. The effect of increased MAV sensory and behavioral capability was demonstrated to be important. Little improvement was observed in swarm performance with these capabilities, however agent performance was adversely affected by reacting to increased knowledge in the wrong way. The utility of MARSS for conducting this type of analysis was demonstrated. |
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