AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Constraint-Based Attribute and Interval Planning
Constraints
Automated Planning: Theory & Practice
Automated Planning: Theory & Practice
Supply chain planning: the role of simulation in advanced planning and scheduling
Proceedings of the 34th conference on Winter simulation: exploring new frontiers
Leap before you look: an effective strategy in an oversubscribed scheduling problem
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
An effective algorithm for project scheduling with arbitrary temporal constraints
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
A comparison of techniques for scheduling earth observing satellites
IAAI'04 Proceedings of the 16th conference on Innovative applications of artifical intelligence
Planning under continuous time and resource uncertainty: a challenge for AI
UAI'02 Proceedings of the Eighteenth conference on Uncertainty in artificial intelligence
Optimal limited contingency planning
UAI'03 Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence
Combining genetic algorithms with squeaky-wheel optimization
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Agent-based simulation for software project planning
WSC '05 Proceedings of the 37th conference on Winter simulation
Understanding performance tradeoffs in algorithms for solving oversubscribed scheduling
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
A constraint-based approach to scheduling an individual's activities
ACM Transactions on Intelligent Systems and Technology (TIST)
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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 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.