Multimodal Vision Research Laboratory

MVRL

Research Area: Reinforcement Learning

Our reinforcement learning research focuses on active search and decision-making in geospatial and visual domains. Recent work includes diffusion-guided visual active search in partially observable environments (DiffVAS), goal modality agnostic active geo-localization (GOMAA-Geo), and active geospatial search for efficient tenant eviction outreach. We also develop partially-supervised reinforcement learning frameworks for visual active search, learning interpretable policies in hindsight-observable POMDPs, and reinforcement learning applications for integrated structural control and health monitoring. Our research addresses challenges in sequential decision-making, exploration strategies, and learning from limited supervision in complex real-world environments.

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Publications

  1. Sarkar A, Sastry S, Pirinen A, Jacobs N, Vorobeychik Y. 2026. DiffVAS: Diffusion-Guided Visual Active Search in Partially Observable Environments. In: International Conference on Autonomous Agents and Multiagent Systems (AAMAS).
    bibtex Reinforcement Learning Remote Sensing GeoAI GenAI
  2. Sarkar A, DiChristofano A, Das S, Fowler P, Jacobs N, Vorobeychik Y. 2025. Active Geospatial Search for Efficient Tenant Eviction Outreach. In: Association for the Advancement of Artificial Intelligence (AAAI).
    code paper bibtex Reinforcement Learning Remote Sensing GeoAI
  3. Thumbnail for GOMAA-Geo: GOal Modality Agnostic Active Geo-localization
    Sarkar A, Sastry S, Pirinen A, Zhang C, Jacobs N, Vorobeychik Y. 2024. GOMAA-Geo: GOal Modality Agnostic Active Geo-localization. In: Neural Information Processing Systems (NeurIPS).
    code paper bibtex Reinforcement Learning Remote Sensing Vision-Language Localization GeoAI
  4. Lanier M, Xu Y, Jacobs N, Zhang C, Vorobeychik Y. 2024. Learning Interpretable Policies in Hindsight-Observable POMDPs through Partially Supervised Reinforcement Learning. In: IEEE International Conference on Machine Learning and Applications.
    paper bibtex Reinforcement Learning
  5. Hormozabad SJ, Jacobs N, Soto MG. 2024. Reinforcement Learning for Integrated Structural Control and Health Monitoring. Practice Periodical on Structural Design and Construction 29. DOI: 10.1061/PPSCFX.SCENG-1455.
    doi bibtex Reinforcement Learning
  6. Sarkar A, Lanier M, Alfeld S, Feng J, Garnett R, Jacobs N, Vorobeychik Y. 2024. A Visual Active Search Framework for Geospatial Exploration. In: IEEE Winter Conference on Applications of Computer Vision (WACV).
    code paper bibtex Reinforcement Learning Remote Sensing GeoAI
  7. Thumbnail for A Partially-Supervised Reinforcement Learning Framework for Visual Active Search
    Sarkar A, Jacobs N, Vorobeychik Y. 2023. A Partially-Supervised Reinforcement Learning Framework for Visual Active Search. In: Neural Information Processing Systems (NeurIPS).
    code paper bibtex Reinforcement Learning Remote Sensing GeoAI