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Terrain exploration carries with it significant hazards. Robots attempting to map a piece of unknown terrain must be able to make decisions and react appropriately to dynamic and potentially hostile conditions. However, because of constraints on size and cost, robots may have limited ability to store and process necessary information. In addition, knowledge discovered by others may be difficult to share. This paper proposes a system using a powerful master controller, operating from a safe environment, directing the movements of numerous robots exploring a piece of terrain. The master controller processes the information from the robots, updates the decision process and distributes these updates back to the robots. This process allows for a cooperative, effective search environment while also maintaining a small processing footprint. It also allows the robot to employ adaptive, subsumptive behavioral modification as new information is made available. A test simulation of a hazardous environment demonstrates that even robots with little intrinsic intelligence can learn complex behaviors in order to reach their goal.