Time Perception: A Review on Psychological, Computational and Robotic Models
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Abstract (arXiv)
Animals exploit time to survive in the world. Temporal information is required for higher-level cognitive abilities such as planning, decision making, communication, and effective cooperation. Since time is an inseparable part of cognition, there is a growing interest in the artificial intelligence approach to subjective time, which has a possibility of advancing the field. The current survey study aims to provide researchers with an interdisciplinary perspective on time perception. Firstly, we introduce a brief background from the psychology and neuroscience literature, covering the characteristics and models of time perception and related abilities. Secondly, we summarize the emergent computational and robotic models of time perception. A general overview to the literature reveals that a substantial amount of timing models are based on a dedicated time processing like the emergence of a clock-like mechanism from the neural network dynamics and reveal a relationship between the embodiment and time perception. We also notice that most models of timing are developed for either sensory timing (i.e. ability to assess an interval) or motor timing (i.e. ability to reproduce an interval). The number of timing models capable of retrospective timing, which is the ability to track time without paying attention, is insufficient. In this light, we discuss the possible research directions to promote interdisciplinary collaboration in the field of time perception.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). First posted on arXiv 23 Jul 2020.
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Citing papers per year: 2022: 2; 2023: 0; 2024: 0; 2025: 1.
3 papers.
- 2022Bayesian sense of time in biological and artificial brainscited by 1
- 2022Predictive Event Segmentation and Representation with Neural Networks: A Self-Supervised Model Assessed by Psychological Experimentscited by 1
- 2025Modulation of temporal decision-making in a deep reinforcement learning agent under the dual-task paradigmcited by 0
- 2025Modulation of temporal decision-making in a deep reinforcement learning agent under the dual-task paradigm3 Nov 2025
- 2022Predictive Event Segmentation and Representation with Neural Networks: A Self-Supervised Model Assessed by Psychological Experiments4 Oct 2022
- 2022Bayesian sense of time in biological and artificial brains14 Jan 2022