Artificial Intelligence - Special issue on knowledge representation
Contingent planning under uncertainty via stochastic satisfiability
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Conditional, probabilistic planning: a unifying algorithm and effective search control mechanisms
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Heuristic search + symbolic model checking = efficient conformant planning
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
Optimal limited contingency planning
UAI'03 Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence
Proceedings of the 40th Conference on Winter Simulation
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Planning, scheduling and effective management of contingencies are crucial for the successful management of construction projects. In this paper we explore a mathematical representation of construction processes that can be used to infer alternative futures of a project as it unfolds. The representation has its foundations in temporal constraint networks. We present algorithms that can traverse the network in time, reason about the constraints driving a construction project, and present the combinatorial possibilities of futures that can emerge from one or more constraint violations during project implementation. The algorithms will aid construction managers to anticipate and react to crisis scenarios as they evolve in time. Our broader goal is to use the contingency information and the user responses to reveal the cognitive strategies used by humans to manage complex crisis scenarios.