Planning the Project Management Way: Efficient Planning by Effective Integration of Causal and Resource Reasoning in RealPlan

Planning the Project Management Way: Efficient Planning by Effective Integration of Causal and Resource Reasoning in RealPlan (2000)

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by Biplav Srivastava , Subbarao Kambhampati , Binh Minh Do

Venue:	Artificial Intelligence
Citations:	30 - 9 self

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Datum	Value	Source
TITLE	Planning the Project Management Way: Efficient Planning by Effective Integration of Causal and Resource Reasoning in RealPlan	SVM HeaderParse 0.1
AUTHOR NAME	Biplav Srivastava	user correction - Legacy Corrections
AUTHOR AFFIL	Department of Computer Science and Engineering,; Arizona State University, Tempe	user correction - Legacy Corrections
AUTHOR ADDR	AZ 85287-5406.	user correction - Legacy Corrections
AUTHOR NAME	Subbarao Kambhampati	user correction - Legacy Corrections
AUTHOR AFFIL	Department of Computer Science and Engineering,; Arizona State University, Tempe	user correction - Legacy Corrections
AUTHOR ADDR	AZ 85287-5406.	user correction - Legacy Corrections
AUTHOR NAME	Binh Minh Do	user correction - Legacy Corrections
AUTHOR AFFIL	Department of Computer Science and Engineering,; Arizona State University, Tempe	user correction - Legacy Corrections
AUTHOR ADDR	AZ 85287-5406.	user correction - Legacy Corrections
ABSTRACT	In most real-world reasoning problems, planning and scheduling phases are loosely coupled. For example, in project planning, the user comes up with a task list and schedules it with a scheduling tool like Microsoft Project. One can view automated planning in a similar way in which there is an action selection phase where actions are selected and ordered to reach the desired goals, and a resource allocation phase where enough resources are assigned to ensure the successful execution of the chosen actions. On the other hand, most existing automated planners studied in Artificial Intelligence do not exploit this loose-coupling and perform both action selection and resource assignment employing the same algorithm. The current work shows that the above strategy severely curtails the scale-up potential of existing state of the art planners which can be overcome by leveraging the loose coupling. Specifically, a novel planning framework called RealPlan is developed in which resource allocatio...	user correction - Legacy Corrections
YEAR	2000	user correction - Legacy Corrections
VENUE	Artificial Intelligence	INFERENCE
VENUE TYPE	JOURNAL	INFERENCE
PAGES	73--134	INFERENCE
VOLUME	131	INFERENCE
TECH	Technical Report	INFERENCE
CITATIONS	57 found	ParsCit 1.0