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Valuing Decisions and Information
Planning under uncertainty is a difficult problem that is of critical importance in the field of robotic exploration. Agents must decide on actions to take that minimize resources expended while maximizing the gain of valuable information. >> continued
Market-Based Multirobot Coordination
This work focusses on developing a market-based architecture that is inherently distributed, but also opportunistically forms centralized sub-groups to improve efficiency, and thus approach optimality. Robots in this architecture are self-interested agents, with the primary goal of maximizing individual profits. >> continued
Self-Scheduling Systems
In many domains, there is a need for computational frameworks and mechanisms that support dynamic coordination of multiple agents toward achievement of specific global objectives over time. Quite often, the problem at hand centers on allocation of the resources that each agent has at its disposal. >> continued
Architecture
The FIRE Project is being built as a distributed three-layered system. >> continued
©2001 Carnegie Mellon University - Robotics Institute