TY - GEN
T1 - An agent-based model of procrastination
AU - Procee, Ruurdje
AU - Kamphorst, Bart A.
AU - van Wissen, Arlette
AU - Meyer, John Jules
PY - 2014
Y1 - 2014
N2 - Procrastination is a widespread type of self-regulation failure that can have serious negative effects on people's health (e.g., because people delay or omit important health behaviors) and well-being. New 'e-coaching' technologies make it possible in principle to offer tailored support to individuals in their efforts to change their self-undermining behavior. In practice, however, such automated support is currently unfeasible because the causal mechanisms behind procrastination are complex and poorly understood. This paper presents a new agent-based model of procrastination that integrates insights from economic models about the dynamics of procrastination with psychological concepts that can help explain the behavior on an individual level. The model is validated by using 5-fold cross validation with simulated annealing to fit and test the parameters on an existing dataset on academic procrastination (n=293). Results show that the agent displays realistic behavior and that the model with the fitted parameters performs significantly better (p<0.01) than the model with randomly selected parameters.
AB - Procrastination is a widespread type of self-regulation failure that can have serious negative effects on people's health (e.g., because people delay or omit important health behaviors) and well-being. New 'e-coaching' technologies make it possible in principle to offer tailored support to individuals in their efforts to change their self-undermining behavior. In practice, however, such automated support is currently unfeasible because the causal mechanisms behind procrastination are complex and poorly understood. This paper presents a new agent-based model of procrastination that integrates insights from economic models about the dynamics of procrastination with psychological concepts that can help explain the behavior on an individual level. The model is validated by using 5-fold cross validation with simulated annealing to fit and test the parameters on an existing dataset on academic procrastination (n=293). Results show that the agent displays realistic behavior and that the model with the fitted parameters performs significantly better (p<0.01) than the model with randomly selected parameters.
UR - http://www.scopus.com/inward/record.url?scp=84923169172&partnerID=8YFLogxK
U2 - 10.3233/978-1-61499-419-0-747
DO - 10.3233/978-1-61499-419-0-747
M3 - Conference contribution
AN - SCOPUS:84923169172
VL - 263
T3 - Frontiers in Artificial Intelligence and Applications
SP - 747
EP - 752
BT - ECAI 2014 - 21st European Conference on Artificial Intelligence, Including Prestigious Applications of Intelligent Systems, PAIS 2014, Proceedings
PB - IOS Press
T2 - 21st European Conference on Artificial Intelligence, ECAI 2014
Y2 - 18 August 2014 through 22 August 2014
ER -