Reinforcement learning in the machine learning world
Can machines or systems interact with agents, including humans, and continually adapt by observing how humans learn in the real world? Professors Michael Littman of Brown University and Charles Isbell of Georgia Tech explore reinforcement…
The intersection of artificial intelligence and robotics
Hear Carnegie Mellon professor Manuela Veloso describe her research on making robots capable of an autonomous cycle of perception, cognition and action, and the journey to understand how algorithms can enable a robot’s sensors to…
SemanticPaint: Interactive 3D Labeling and Learning at your Fingertips
We present a new interactive and online approach to 3D scene understanding. Our system, SemanticPaint, allows users to simultaneously scan their environment, whilst interactively segmenting the scene simply by reaching out and touching any desired…