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Project Details
Description (abstract)
Human performance in apparently simple tasks like walking in a crowd, bicycling and driving, is deeply impressive. We learn these kinds of tasks efficiently, and cope under a variety of conditions., but this adaptability is in contrast to current AI and robotics, where the complexity and ambiguity of the real world have turned out to be huge challenges. This suggests that the human brain has evolved techniques for organizing perception and action that may be different from current AI. This research explores the hypothesis that a highly efficient representation of space underlies human adaptability. It combines computational and experimental methods to investigate how our cognitive system creates this “sense of space”. The integrative approach that takes the research beyond the state-of-the-art is how data from multiple experimental tasks derived from analysis of natural task constraints are used to constrain the development of fully implemented unified models of cognition.
Layman's description
Human performance in apparently simple tasks like walking in a crowd, bicycling and driving, is deeply impressive. We learn these kinds of tasks efficiently, and cope under a variety of conditions., but this adaptability is in contrast to current AI and robotics, where the complexity and ambiguity of the real world have turned out to be huge challenges. This suggests that the human brain has evolved techniques for organizing perception and action that may be different from current AI. This research explores the hypothesis that a highly efficient representation of space underlies human adaptability. It combines computational and experimental methods to investigate how our cognitive system creates this “sense of space”. The integrative approach that takes the research beyond the state-of-the-art is how data from multiple experimental tasks derived from analysis of natural task constraints are used to constrain the development of fully implemented unified models of cognition.
Status | Active |
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Effective start/end date | 01/09/2020 → 31/08/2025 |
Funding
- Academy of Finland
Fields of Science
- 6162 Cognitive science
Projects
- 1 Active
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UPP-PERFORMANCE: Human Performance in Complex Dynamic Tasks - A Unified Predictive Processing Approach
Lappi, O., Pekkanen, J., Tuhkanen, S., Rinkkala, P. J., Frantsi, R. M. & Palomäki, J. P.
01/09/2019 → 31/08/2023
Project: Research project
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Gaze Strategies in Driving: An Ecological Approach
Lappi, O., 14 Mar 2022, In: Frontiers in Psychology. 13, 15 p., 821440.Research output: Contribution to journal › Review Article › peer-review
Open AccessFile -
Tracking an occluded visual target with sequences of saccades
Tammi, T., Pekkanen, J., Tuhkanen, S., Oksama, L. & Lappi, O., 19 Jan 2022, In: Journal of Vision. 22, 1, 16 p.Research output: Contribution to journal › Article › Scientific › peer-review
Open AccessFile -
Action control, forward models and expected rewards: representations in reinforcement learning
Rusanen, A-M., Lappi, O., Kuokkanen, J. & Pekkanen, J., 2021, In: Synthese. 199, p. 14017–14033 17 p.Research output: Contribution to journal › Article › Scientific › peer-review
Open AccessFile