University of Oulu

Sakcak, B., Weinstein, V., LaValle, S.M. (2023). The Limits of Learning and Planning: Minimal Sufficient Information Transition Systems. In: LaValle, S.M., O’Kane, J.M., Otte, M., Sadigh, D., Tokekar, P. (eds) Algorithmic Foundations of Robotics XV. WAFR 2022. Springer Proceedings in Advanced Robotics, vol 25. Springer, Cham.

The limits of learning and planning : minimal sufficient information transition systems

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Author: Sakcak, Basak1; Weinstein, Vadim1; LaValle, Steven M.1
Organizations: 1Faculty of Information Technology and Electrical Engineering, Center for Ubiquitous Computing, University of Oulu, Oulu, Finland
Format: article
Version: accepted version
Access: embargoed
Persistent link:
Language: English
Published: Springer Nature, 2023
Publish Date: 2023-12-15


In this paper, we view a policy or plan as a transition system over a space of information states that reflect a robot’s or other observer’s perspective based on limited sensing, memory, computation, and actuation. Regardless of whether policies are obtained by learning algorithms, planning algorithms, or human insight, we want to know the limits of feasibility for given robot hardware and tasks. Toward the quest to find the best policies, we establish in a general setting that minimal information transition systems (ITSs) exist up to reasonable equivalence assumptions, and are unique under some general conditions. We then apply the theory to generate new insights into several problems, including optimal sensor fusion/filtering, solving basic planning tasks, and finding minimal representations for feasible policies.

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Series: Springer proceedings in advanced robotics
ISSN: 2511-1256
ISSN-E: 2511-1264
ISSN-L: 2511-1256
ISBN: 978-3-031-21090-7
ISBN Print: 978-3-031-21089-1
Volume: 25
Pages: 256 - 272
DOI: 10.1007/978-3-031-21090-7_16
Host publication: Algorithmic Foundations of Robotics XV. WAFR 2022 : Proceedings of the Fifteenth Workshop on the Algorithmic Foundations of Robotics
Host publication editor: LaValle, Steven M.
O’Kane, Jason M.
Otte, Michael
Sadigh, Dorsa
Tokekar, Pratap
Conference: International Workshop on the Algorithmic Foundations of Robotics
Type of Publication: A4 Article in conference proceedings
Field of Science: 113 Computer and information sciences
Funding: This work was supported by a European Research Council Advanced Grant (ERC AdG, ILLUSIVE: Foundations of Perception Engineering, 101020977), Academy of Finland (projects PERCEPT 322637, CHiMP 342556), and Business Finland (project HUMOR 3656/31/2019).
Copyright information: © 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG