Amanda Prorok
Professor of Collective Intelligence and Robotics
Leads the Prorok Lab on multi-robot systems, learning coordination policies for robot collectives with applications to logistics, transport and robotic fleets.
Amanda Prorok's lab at Cambridge works on planning, control & multi-robot systems. 27 papers since 2023, 23 at top venues, mostly ICLR and NeurIPS. 7 PhD students. 10 alumni. Applications close .
At a glance
- papers, 2023–2026
- 7/ year
- at T1 venues
- 85%
- PhD students
- 7
- MS students
- 0
- alumni listed
- 10
Papers by yearfrom the lab homepage, 2023–2026
- 10 papers2026 · T1 7 · collecting
- 8 papers2025 · T1 8
- 5 papers2024 · T1 4
- 4 papers2023 · T1 4
T1 venuesOtherVenues: ICLR, NeurIPS, CoRL, ICRA, T-RO
Research focuspaper titles that use each topic's words
- Planning, control & multi-robot systems22 papers
- coordination1 paper
- policies1 paper
- multi-robot systems0 papers
- transport0 papers
Paper list
From the lab homepage.
202610 papers
- npj RoboticsConcrete multi-agent path planning enabling kinodynamically aggressive maneuvers
- ICAPSdb-LaCAM: Fast and Scalable Multi-Robot Kinodynamic Motion Planning with Discontinuity-Bounded Search and Lightweight MAPF
- T-RO (T1)Denoising Multi-Robot Trajectories
- NeurIPS (T1)Events as Triggers for Behavioral Diversity in Multi-Agent Reinforcement Learning
- NeurIPS (T1)Generalized Intention Modeling in Multi-Agent Reinforcement Learning
- AAAI (T1)Graph Attention-Guided Search for Dense Multi-Agent Pathfinding
- ICLR (T1)Pairwise is Not Enough: Hypergraph Neural Networks for Multi-Agent Pathfinding
- RA-LPrompting Robot Teams with Natural Language
- ICLR (T1)Remotely Detectable Robot Policy Watermarking
- ICLR (T1)When Is Diversity Rewarded in Cooperative Multi-Agent Learning?
20258 papers
- T-RO (T1)Co-Optimizing Reconfigurable Environments and Policies for Decentralized Multi-Agent Navigation
- IROS (T1)D4orm: Multi-Robot Trajectories with Dynamics-aware Diffusion Denoised Deformations
- ICRA (T1)DVM-SLAM: Decentralized Visual Monocular Simultaneous Localization and Mapping for Multi-Agent Systems
- ICLR (T1)Efficient Model-Based Reinforcement Learning Through Optimistic Thompson Sampling
- Science Robotics (T1)Extending robot minds through collective learning
- ICRA (T1)Language-Conditioned Offline RL for Multi-Robot Navigation
- NeurIPS (T1)No-Regret Thompson Sampling for Finite-Horizon Markov Decision Processes with Gaussian Processes
- CoRL (T1)ReCoDe: Reinforcement Learning-based Dynamic Constraint Design for Multi-Agent Coordination
20245 papers
- JMLR (T1)BenchMARL: Benchmarking Multi-Agent Reinforcement Learning
- ICML (T1)Controlling Behavioral Diversity in Multi-Agent Reinforcement Learning
- CoRL (T1)CoViS-Net: A Cooperative Visual Spatial Foundation Model for Multi-Robot Applications
- CoRL (T1)Provably Safe Online Multi-Agent Navigation in Unknown Environments
- DARSThe Cambridge RoboMaster: An Agile Multi-Robot Research Platform
20234 papers
- NeurIPS (T1)Generalised f-Mean Aggregation for Graph Neural Networks
- AAMAS (T1)Heterogeneous multi-robot reinforcement learning
- ICLR (T1)POPGym: Benchmarking Partially Observable Reinforcement Learning
- NeurIPS (T1)Reinforcement Learning with Fast and Forgetful Memory
Where alumni went10 listed
Apply to CambridgeMichaelmas 2027
PhD in Computer Science
- Round
- Funding round (8 Dec 2026)
- Opens
- GRE
- See program page
- English
- See program page
- Fee
- See program page
Confirmed on the program page.
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- Papers
- The lab homepage
- Members
- Lab homepage
- Alumni
- Lab homepage
Tiers are venue classifications, not lab rankings.
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