Beyond spatial reasoning: Challenges for ecological problem solving

Abstract

This vision piece reflects upon virtues of early computer science due to scarcity and high cost of computational resources. It critically assesses divergences between real-world problems and their computational counterparts in commonsense problem solving. The paper points out the different objectives of commonsense versus scientific approaches to problem solving. It describes how natural cognitive systems exploit space and time without explicitly representing their properties and why purely computational approaches are less efficient than their natural role models, as they depend on explicit representations. We argue for investigating spatio-temporally integrated methods to spatial problem solving. We contrast these methods to sequential computational approaches that require digital twins of the environment and cannot make direct use of simultaneous spatio-temporal interactions. The paper concludes with predicting future developments in problem solving, praising the relative merits of different routes to be taken. It advocates the translation of fundamental cognitive principles into technical robotic solutions.

Keywords

• artificial intelligence
• cognitive system
• commonsense problem solving
• learning from nature
• perception and action
• spatial organization
• spatial cognition
• affordance
• coarse to fine processing