Towards a Quantum-Like Cognitive Architecture for Decision-Making
This work addresses cognitive science and AI researchers by offering a novel theoretical approach to decision-making, but it appears incremental as it builds on existing quantum-like models without demonstrating broad empirical validation.
The authors tackled the problem of modeling cognitive biases in decision-making by proposing a quantum mechanics-based framework that generalizes classical models and predicts biases without relying on heuristics or assumptions about computational resources, though no concrete numerical results are provided.
We propose an alternative and unifying framework for decision-making that, by using quantum mechanics, provides more generalised cognitive and decision models with the ability to represent more information than classical models. This framework can accommodate and predict several cognitive biases reported in Lieder & Griffiths without heavy reliance on heuristics nor on assumptions of the computational resources of the mind.