Simulating Human Routines

Integrating Social Practice Theory in Agent-Based Models

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Abstract

Our routines play an important role in a wide range of social challenges such as climate change, disease outbreaks and coordinating the staff and patients of a hospital. Studying these systems via agent-based simulations (ABS) enables researchers to gain insight into complex aspects of these challenges such as human interaction, learning, heterogeneity, feedback loops and emergence. Current agent frameworks do not integrate social and psychological evidence on human routines: humans make habitual decisions, interconnect these habits throughout the day and use these interconnected habits as a blueprint for social interaction. This thesis provides the domain-independent SoPrA (Social Practice Agent) framework that integrates theories on social practices to support the simulation of human routines. Social practice theory is a socio-cognitive theory applicable to model human routines as the theory aims to describe our ‘daily doings and sayings’. The first part of the thesis identifies the aspects of social practice theory that are relevant for agent-based simulation, distils requirements from the literature, reviews current agent models and provides the SoPrA framework that satisfies said requirements. The second part describes applications of SoPrA on the value-alignment problem in AI, identifying social bottlenecks in hospitals and comparing theories on how habits break. This results in an agent framework with a clear relation to current evidence and, due to its modularity and focus on domain-independence, is usable for a wide range of ABS studies that involve human routines. As such, SoPrA is relevant for scientific work in (1) ABS by enabling a new way to know, explore and improve the world, grounded in evidence on human routines; (2) in multi-agent systems by enabling agents that understand and interact with human routines; and (3) in the social sciences by crystallizing theories on human routines and enabling exploration of these theories via simulation. Furthermore, this thesis shows the societal relevance of SoPrA for understanding and improving the role of routines in AI safety, emergency rooms, commuting behaviour and consumption behaviour.