Anja Zöller

Agent-Based Patient Scheduling in Hospitals

Patient scheduling in hospitals is a very complex task. This complexity stems from the distributed structure of hospitals and the dynamics of the treatment process. Hospitals consist of various autonomous, administratively distinct units which are visited by the patients according to their individual disease. However, the pathways (the needed medical actions) and the medical priorities (the health condition of the patients) are likely to change due to new findings about the diseases of the patients during examination. Moreover, the durations of the treatments and examinations are stochastic. Additional problems for patient scheduling in hospitals arise from complications and emergencies. Thus, patient scheduling in hospitals requires a distributed and flexible approach. To this end, a flexible, agent-based approach to patient scheduling is developed in this chapter. After a description of the addressed patient scheduling problem, the proposed mechanism for patient-scheduling is presented and evaluated.

Patient scheduling under uncertainty

Patient scheduling in hospitals is faced with a high amount ofcomplexity [4][5] due tothe inherent dynamics of the processes andthe distributed organisation structure of hospitals. For treatment,patients visit different units according to their illness [7]. However,the necessary medical treatments are often not completely deter-mined at the beginning of the treatment process [5]. Further, theduration of the treatments are stochastic. Therefore, the main con-tribution of this paper is the introduction of MedPAge

Benchmarking of Multiagent Systems

This chapter introduces benchmarking as a special form of evaluation and addresses problems and demands concerning the benchmarking of multiagent systems. It gives an overview of the evaluation concepts used in the German research program SPP 1083 for intelligent agents and realistic commercial application scenarios as well as examples for evaluation and benchmark studies for multiagent systems. The article provides basics for setting-up evaluation studies, regarding special concerns for the evaluation of multiagent systems. Moreover, the exemplary overview may serve as orientation for further evaluation and benchmarking of multiagent systems in realistic and commercial application scenarios.