Knowledge & Cognition
Long-term decision-related activities, such as bottom-up and top-down policy development, analysis, and planning, stand to benefit from the creation and application of knowledge-based cognitive multi-agent decision support systems that would be capable of representing real-world spatiotemporal social human behavior in local contexts. However, limitations in our ability to represent the knowledge and cognition of real-world decision-makers have hindered the development of such models.
This article describes and provides theoretical foundations of a framework for representing knowledge and cognition of boundedly-rational decision-makers in social contexts, which is one of the SOSIEL toolkit’s six integral components. A SOSIEL agent’s knowledge is stored by its cognitive architecture’s memory component, is modified by its learning component, and is used by its decision-making component in making decisions. The framework helps us move towards overcoming challenges in representing knowledge and cognition of boundedly-rational decision-making and, in combination with the other components in the SOSIEL toolkit, moves us closer towards developing models that are capable of assisting policy development, analysis, and planning.