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Found 5 papers, 4 papers with code
Deep Reinforcement Learning for Multi-Agent Interaction
The development of autonomous agents which can interact with other agents to accomplish a given task is a core area of research in artificial intelligence and machine learning.
Verifiable Goal Recognition for Autonomous Driving with Occlusions
Goal recognition (GR) involves inferring the goals of other vehicles, such as a certain junction exit, which can enable more accurate prediction of their future behaviour.
GRIT: Fast, Interpretable, and Verifiable Goal Recognition with Learned Decision Trees for Autonomous Driving
As autonomous driving is safety-critical, it is important to have methods which are human interpretable and for which safety can be formally verified.
Autonomous Driving
Robotics
Multiagent Systems
Integrating Planning and Interpretable Goal Recognition for Autonomous Driving
The ability to predict the intentions and driving trajectories of other vehicles is a key problem for autonomous driving.
Robotics
Non-Intrusive Load Monitoring with Fully Convolutional Networks
Non-intrusive load monitoring or energy disaggregation involves estimating the power consumption of individual appliances from measurements of the total power consumption of a home.
