Interleaving Fast and Slow Decision Making
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Abstract (arXiv)
The "Thinking, Fast and Slow" paradigm of Kahneman proposes that we use two different styles of thinking -- a fast and intuitive System 1 for certain tasks, along with a slower but more analytical System 2 for others. While the idea of using this two-system style of thinking is gaining popularity in AI and robotics, our work considers how to interleave the two styles of decision-making, i.e., how System 1 and System 2 should be used together. For this, we propose a novel and general framework which includes a new System 0 to oversee Systems 1 and 2. At every point when a decision needs to be made, System 0 evaluates the situation and quickly hands over the decision-making process to either System 1 or System 2. We evaluate such a framework on a modified version of the classic Pac-Man game, with an already-trained RL algorithm for System 1, a Monte-Carlo tree search for System 2, and several different possible strategies for System 0. As expected, arbitrary switches between Systems 1 and 2 do not work, but certain strategies do well. With System 0, an agent is able to perform better than one that uses only System 1 or System 2.
Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). First posted on arXiv 30 Oct 2020.
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Citing papers per year: 2021: 1; 2022: 1; 2023: 0; 2024: 3.
5 papers.
- 2021Thinking Fast and Slow in AI: the Role of Metacognitioncited by 11
- 2024Towards Building Specialized Generalist AI with System 1 and System 2 Fusioncited by 8
- 2024Multi-Agent Trajectory Prediction with Difficulty-Guided Feature Enhancement Networkcited by 6
- 2022Combining Fast and Slow Thinking for Human-like and Efficient Navigation in Constrained Environmentscited by 5
- 2024Improving deep learning with prior knowledge and cognitive models: A survey on enhancing explainability, adversarial robustness and zero-shot learningcited by 4
- 2024Multi-Agent Trajectory Prediction with Difficulty-Guided Feature Enhancement Network26 Jul 2024
- 2024Towards Building Specialized Generalist AI with System 1 and System 2 Fusion11 Jul 2024
- 2024Improving deep learning with prior knowledge and cognitive models: A survey on enhancing explainability, adversarial robustness and zero-shot learning11 Mar 2024
- 2022Combining Fast and Slow Thinking for Human-like and Efficient Navigation in Constrained Environments18 Jan 2022
- 2021Thinking Fast and Slow in AI: the Role of Metacognition5 Oct 2021