[Paper Review] Control of mental representations in human planning.

Mark K. Ho, David Abel+4 more|arXiv (Cornell University)|May 14, 2021

Complex Systems and Decision Making20 references4 citations

TL;DR

This paper proposes that humans actively control their mental representations during planning—a process called 'construal'—to balance representational complexity and planning utility. Using pre-registered behavioral experiments and a formal model, it demonstrates that people online apply cognitive control to shape these representations in value-guided ways, enabling efficient and flexible problem-solving under cognitive constraints.

ABSTRACT

One of the most striking features of human cognition is the capacity to plan. Two aspects of human planning stand out: its efficiency, even in complex environments, and its flexibility, even in changing environments. Efficiency is especially impressive because directly computing an optimal plan is intractable, even for modestly complex tasks, and yet people successfully solve myriad everyday problems despite limited cognitive resources. Standard accounts in psychology, economics, and artificial intelligence have suggested this is because people have a mental representation of a task and then use heuristics to plan in that representation. However, this approach generally assumes that mental representations are fixed. Here, we propose that mental representations can be controlled and that this provides opportunities to adaptively simplify problems so they can be more easily reasoned about -- a process we refer to as construal. We construct a formal model of this process and, in a series of large, pre-registered behavioral experiments, show both that construal is subject to online cognitive control and that people form value-guided construals that optimally balance the complexity of a representation and its utility for planning and acting. These results demonstrate how strategically perceiving and conceiving problems facilitates the effective use of limited cognitive resources.

Motivation & Objective

• To investigate whether mental representations in human planning are fixed or subject to active cognitive control.
• To examine how people adaptively simplify problems by strategically shaping their mental representations during planning.
• To test whether such representation control is guided by value, optimally balancing utility and complexity.
• To develop and validate a formal model of adaptive construal in human decision-making.

Proposed method

• Developing a formal computational model of construal as a process of online, value-guided simplification of task representations.
• Designing large-scale, pre-registered behavioral experiments to measure how participants form and use mental representations in dynamic planning tasks.
• Using model-based analysis to infer participants' construal strategies from their choices and response times.
• Applying inverse reinforcement learning techniques to estimate utility functions guiding representation formation.
• Testing whether representation control is sensitive to cognitive load and task demands, indicating online control.

Experimental results

Research questions

• RQ1 Can people actively control their mental representations during planning, or are they fixed?
• RQ2 Is the formation of mental representations in planning guided by value, balancing utility and complexity?
• RQ3 Does cognitive control enable real-time adaptation of representations to optimize planning efficiency?
• RQ4 How do people trade off representational simplicity against accuracy in dynamic environments?

Key findings

• Participants actively control their mental representations during planning, demonstrating online cognitive control over construal.
• Mental representations are formed in a value-guided manner, optimally balancing complexity and utility for planning.
• People adapt their representations in response to task demands, showing strategic simplification to manage cognitive load.
• The formal model of construal successfully predicts human behavior across multiple experimental conditions.
• Construal is sensitive to both task structure and cognitive constraints, indicating flexible, goal-directed control.
• The results support a framework in which strategic perception and conception of problems are central to efficient cognition.