Name
Abstract | ||
|---|---|---|
We present a Markov Decision Process (MDP) approach to compute policies that can aid the management of human weight loss. We show that the problem can be formulated as a Markov Chain under a reasonable set of assumptions. The states represent the quantized weight of a participant. The transitions between the states represent nutrition and exercise actions. A policy computed using this model represents an intervention strategy for a participant. Given the participant's initial weight and target weight, we show that the computed policy is sensitive to the reward functions that are associated with the actions. In the future, such an approach can be used to offer wellness interventions to participants. |
Year | Venue | Field |
|---|---|---|
2016 | 2016 ANNUAL IEEE SYSTEMS CONFERENCE (SYSCON) | Mathematical optimization,Psychological intervention,Markov process,Markov model,Partially observable Markov decision process,Markov chain,Markov decision process,Control engineering,Variable-order Markov model,Engineering,Weight loss |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
3 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chippa, Mukesh K. | 1 | 1 | 1.11 |
| Shivakumar Sastry | 2 | 79 | 13.63 |