Depth-first iterative-deepening: an optimal admissible tree search
Artificial Intelligence
Principles of artificial intelligence
Principles of artificial intelligence
Real-time knowledge-based systems
AI Magazine
What AI can do for battle management
AI Magazine
Optimization of query evaluation algorithms
ACM Transactions on Database Systems (TODS)
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
A Formal Model of Trade-off between Optimization and Execution Costs in Semantic Query Optimization
VLDB '88 Proceedings of the 14th International Conference on Very Large Data Bases
Decision-Theoretic Control of Reasoning: General Theory and an
Decision-Theoretic Control of Reasoning: General Theory and an
New optimization techniques in database access and maintenance
New optimization techniques in database access and maintenance
QUIST: a system for semantic query optimization in relational databases
VLDB '81 Proceedings of the seventh international conference on Very Large Data Bases - Volume 7
Monitoring the progress of anytime problem-solving
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
Can real-time search algorithms meet deadlines?
AAAI'92 Proceedings of the tenth national conference on Artificial intelligence
Heuristic search when time matters
Journal of Artificial Intelligence Research
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Real time artificial intelligence (AI) systems are required to respond within a given deadline, or have optimal response times. While some researchers have addressed the issue of planning under deadline constraints, there has been very little research towards optimizing the response time of problem-solving methods. The costs for a response consists of the cost to plan for a solution and the cost of executing the chosen solution. There is an intimate trade-off between these two costs. This paper presents an algorithm for providing near optimal response times by formalizing the trade-offs between planning and execution costs. We provide a proof of correctness and describe an implementation of the algorithm in a real time application of query planning. We also provide a model for considering response times in the context of the A* heuristic search algorithm.