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Planning

Reinforcement Learning in the Wind

Deep reinforcement learning is an AI technique for choosing how to act in different situations repeatedly occurring over time. It has shown tremendous success in playing games, such as ATARI video games, chess, Go, and StarCraft, going as far as beating professional human players. While games present certain interesting scientific …

ICAPS Workshops

The list of workshops for the ICAPS conference in Delft (June 25-26 2018) has been published. All have deadlines early March 2018 and notifications in April. Please click the links below for details. Acronym Workshop Organizers COPLAS Constraint Satisfaction Techniques for Planning and Scheduling Roman Bartak Miguel Salido HSDIP Heuristics …

Scientific advisor at Dutch Railways (NS)

Last week I started at the Dutch Railways in Bob Huisman’s group on Maintenance Research and Development as a scientific advisor, for one day a week. My aim is to support and further increase the exchange of knowledge and experience between Dutch Railways and Delft University of Technology. I aim …

Solving Road Congestion Problems with Algorithms?

State-of-the-art in-car navigation systems contribute to preventing road congestion, because avoiding traffic jams helps dissolving it. Currently, the more advanced systems already are using both historic travel times as well as recently observed travel times to estimate future travel times for road segments, and base their route navigation advice upon …