The curse of variety in transportation systems
Assistant Professor Cathy Wu is addressing traffic control problems by leveraging deep reinforcement learning.
Topic
Laboratory for Information and Decision Systems (LIDS)
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A simpler method for learning to control a robot
Researchers develop a machine-learning technique that can efficiently learn to control a robot, leading to better performance with fewer data.
3 Questions: Honing robot perception and mapping
Luca Carlone and Jonathan How of MIT LIDS discuss how future robots might perceive and interact with their environment.
A step toward safe and reliable autopilots for flying
A new AI-based approach for controlling autonomous robots satisfies the often-conflicting goals of safety and stability.
Exploring new methods for increasing safety and reliability of autonomous vehicles
A new study finds human supervisors have the potential to reduce barriers to deploying autonomous vehicles.
Three MIT-led projects awarded MURI funding for 2023
Through the Multidisciplinary University Research Initiative, the US Department of Defense supports research projects in areas of critical importance to national defense.
A better way to study ocean currents
A new machine-learning model makes more accurate predictions about ocean currents, which could help with tracking plastic pollution and oil spills, and aid in search and rescue.
The answer may be blowing in the wind
The MIT Energy Initiative’s Spring Symposium highlights the vast potential of offshore turbines in decarbonizing the grid.
Researchers create a tool for accurately simulating complex systems
The system they developed eliminates a source of bias in simulations, leading to improved algorithms that can boost the performance of applications.
Martin Wainwright named director of the Institute for Data, Systems, and Society
Widely recognized leader in statistics and machine learning to succeed Munther Dahleh.
An interdisciplinary approach to fighting climate change through clean energy solutions
Principal Research Scientist Audun Botterud tackles a range of cross-cutting problems — from energy market interactions to designing batteries — to get closer to a decarbonized power grid.
A method for designing neural networks optimally suited for certain tasks
With the right building blocks, machine-learning models can more accurately perform tasks like fraud detection or spam filtering.
New algorithm keeps drones from colliding in midair
Researchers create a trajectory-planning system that enables drones working together in the same airspace to always choose a safe path forward.
Strengthening trust in machine-learning models
Associate Professor Tamara Broderick and colleagues build a “taxonomy of trust” to identify where confidence in the results of a data analysis might break down.
New “traffic cop” algorithm helps a drone swarm stay on task
By keeping data fresh, the system could help robots inspect buildings or search disaster zones.