DC Field | Value | Language |
---|---|---|
dc.contributor.author | Shin, Kyohong | ko |
dc.contributor.author | Lee, Taesik | ko |
dc.date.accessioned | 2019-06-10T05:10:04Z | - |
dc.date.available | 2019-06-10T05:10:04Z | - |
dc.date.created | 2019-06-10 | - |
dc.date.created | 2019-06-10 | - |
dc.date.issued | 2019-06-01 | - |
dc.identifier.citation | 4th International Conference on Health Care Systems Engineering, HCSE 2019, pp.103 - 115 | - |
dc.identifier.issn | 2194-1009 | - |
dc.identifier.uri | http://hdl.handle.net/10203/262499 | - |
dc.description.abstract | We present a finite-horizon Markov Decision Process (MDP) model for a patient prioritization and hospital selection problem, which is a critical decision-making problem in emergency medical service operation. Solving this model requires reinforcement learning (RL) due to its large state space. We propose a novel approach with an aim to significantly enhance the scalability of RL algorithms. Our approach, which we call a State Partitioning and Action Network, SPartAN in short, is a meta-algorithm that offers a framework an RL algorithm can be incorporated into. In this approach, we partition the state space into smaller subspaces to construct a reliable action network in the downstream subspace. This action network is then used in a simulation to approximate values of the upstream subspace. Using temporal difference (TD) learning as an example RL algorithm, we show that SPartAN is able to reliably derive a high-quality policy solution, thereby opening opportunities to solve many practical MDP models in healthcare system problems. | - |
dc.language | English | - |
dc.publisher | International Conference on Health Care Systems Engineering | - |
dc.title | A Meta Algorithm For Reinforcement Learning: Emergency Medical Service Resource Prioritization Problem in an MCI as an example | - |
dc.type | Conference | - |
dc.identifier.scopusid | 2-s2.0-85084000433 | - |
dc.type.rims | CONF | - |
dc.citation.beginningpage | 103 | - |
dc.citation.endingpage | 115 | - |
dc.citation.publicationname | 4th International Conference on Health Care Systems Engineering, HCSE 2019 | - |
dc.identifier.conferencecountry | CN | - |
dc.identifier.conferencelocation | CHU Sainte-Justine, Montreal | - |
dc.identifier.doi | 10.1007/978-3-030-39694-7_9 | - |
dc.contributor.localauthor | Lee, Taesik | - |
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