Habitual Behavior

Habitual behavior research focuses on understanding how repetitive actions become ingrained, influencing decision-making and shaping individual patterns. Current studies employ diverse approaches, including agent-based modeling, LSTM and transformer neural networks for analyzing sequential data (like smartphone app usage), and Markov models for tracking behavioral changes over time. This research is significant for improving predictions of user engagement in various contexts (e.g., social media, human-robot interaction), developing more efficient and personalized AI systems, and providing objective measures for monitoring behavioral changes in populations like those with dementia.