Multiscale Decision Making for Multiple Decision Alternatives
| dc.contributor.author | Sudhaakar, Swathi Priyadarshini | en |
| dc.contributor.committeechair | Wernz, Christian | en |
| dc.contributor.committeemember | Taaffe, Michael R. | en |
| dc.contributor.committeemember | Bish, Ebru K. | en |
| dc.contributor.department | Industrial and Systems Engineering | en |
| dc.date.accessioned | 2013-02-19T22:39:40Z | en |
| dc.date.available | 2013-02-19T22:39:40Z | en |
| dc.date.issued | 2013-01-24 | en |
| dc.description.abstract | In organizations with decision makers across multiple hierarchical levels, conflicting objectives are commonly observed. The decision maker, or agent, at the highest level usually makes decisions in the interest of the organization, while a subordinate agent may have a conflict of interest between taking a course of action that is best for the organization and the course of action that is best for itself. The Multiscale Decision-Making (MSDM) model was established by Wernz (2008). The model has been developed to capture interactions in multi-agent systems, by integrating both the hierarchical and temporal scale of decisions made in organizations. This thesis contributes towards expanding the results in the hierarchical interaction domain of MSDM by extending the model to incorporate N decision alternatives and outcomes instead of two, and studying its effect on the interaction between agents. We consider decisions with uncertain outcomes, where the outcomes of the decisions made by agents lower in hierarchy affect the transition probabilities of the decisions made by agents above them in hierarchy. This leads to a game theoretic situation, where the lower-level agents need to be sufficiently incentivized in order to shift their best response strategy to one in the interest of their superior and the organization. Mathematical expressions for the optimal incentives at each hierarchical level are developed. We analyze systems with agents interacting across two and three organizational levels. We then study the effect of introducing the cost of taking an action on the optimal incentives. We discuss a health care application of MSDM. | en |
| dc.description.degree | Master of Science | en |
| dc.format.medium | ETD | en |
| dc.identifier.other | vt_gsexam:240 | en |
| dc.identifier.uri | http://hdl.handle.net/10919/19236 | en |
| dc.publisher | Virginia Tech | en |
| dc.rights | In Copyright | en |
| dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | en |
| dc.subject | Multiscale Decision-Making | en |
| dc.subject | Decision Analysis | en |
| dc.subject | Optimal Incentives | en |
| dc.subject | Hierarchical Agents | en |
| dc.subject | Health Care Decision Support | en |
| dc.title | Multiscale Decision Making for Multiple Decision Alternatives | en |
| dc.type | Thesis | en |
| thesis.degree.discipline | Industrial and Systems Engineering | en |
| thesis.degree.grantor | Virginia Polytechnic Institute and State University | en |
| thesis.degree.level | masters | en |
| thesis.degree.name | Master of Science | en |
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