Time and resource limitations mean that current Mars rovers (and any future planetary rovers) cannot hope to achieve every desirable scientific goal. We must therefore select and plan for a subset of the possible experiments, maximizing some utility metric. The use of simulation in planning is appealing because of its potential for representing complex, realistic details about the rover and its environment. We demonstrate a planning algorithm that performs high-level planning in a space of plan

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... strategies, rather than actual plans. In the current implementation, candidate strategies are evaluated by a simple simulation, and a genetic algorithm is used to search for effective strategies. Preliminary results are encouraging, particularly the potential for modeling uncertainty about the time required to complete actions, and the ability to develop strategies that can deal with this uncertainty gracefully.