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Found 5 papers, 3 papers with code
A Domain-Agnostic Approach for Characterization of Lifelong Learning Systems
Despite the advancement of machine learning techniques in recent years, state-of-the-art systems lack robustness to "real world" events, where the input distributions and tasks encountered by the deployed systems will not be limited to the original training context, and systems will instead need to adapt to novel distributions and tasks while deployed.
Sequential Online Chore Division for Autonomous Vehicle Convoy Formation
Chore division is a class of fair division problems in which some undesirable "resource" must be shared among a set of participants, with each participant wanting to get as little as possible.
A Scavenger Hunt for Service Robots
In this problem, the goal is to find a set of objects as quickly as possible, given probability distributions of where they may be found.
Scalable Multiagent Driving Policies For Reducing Traffic Congestion
Next, we propose a modular transfer reinforcement learning approach, and use it to scale up a multiagent driving policy to outperform human-like traffic and existing approaches in a simulated realistic scenario, which is an order of magnitude larger than past scenarios (hundreds instead of tens of vehicles).
Improving Grounded Natural Language Understanding through Human-Robot Dialog
Natural language understanding for robotics can require substantial domain- and platform-specific engineering.
