Can AI planners solve practical problems?
Computational Intelligence
Associating AI Planner Entities with an Underlying Time Point Network
EWSP '91 Proceedings of the European Workshop on Planning
Planning and Scheduling Patient Tests in Hospital Laboratories
AIME '97 Proceedings of the 6th Conference on Artificial Intelligence in Medicine in Europe
Plan management in the medical domain
AI Communications
Planning with sharable resource constraints
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Temporal reasoning for decision support in medicine
Artificial Intelligence in Medicine
Adaptive resource allocation for efficient patient scheduling
Artificial Intelligence in Medicine
A hybrid tabu search algorithm for automatically assigning patients to beds
Artificial Intelligence in Medicine
One hyper-heuristic approach to two timetabling problems in health care
Journal of Heuristics
Knowledge-Driven adaptive execution of care pathways based on continuous planning techniques
BPM' 2012 Proceedings of the 2012 international conference on Process Support and Knowledge Representation in Health Care
Artificial Intelligence in Medicine
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Hospital laboratories perform examination tests upon patients, in order to assist medical diagnosis or therapy progress. Planning and scheduling patient requests for examination tests is a complicated problem because it concerns both minimization of patient stay in hospital and maximization of laboratory resources utilization. In the present paper, we propose an integrated patient-wise planning and scheduling system which supports the dynamic and continual nature of the problem. The proposed combination of multiagent and blackboard architecture allows the dynamic creation of agents that share a set of knowledge sources and a knowledge base to service patient test requests.