—Reinforcement learning is the scheme for unsupervised learning in which robots are expected to acquire behavior skills through self-explorations based on reward signals. There a...
Hiroaki Arie, Tetsuya Ogata, Jun Tani, Shigeki Sug...
Markovian processes have long been used to model stochastic environments. Reinforcement learning has emerged as a framework to solve sequential planning and decision-making proble...
Design and development of novel human-computer interfaces poses a challenging problem: actions and intentions of users have to be inferred from sequences of noisy and ambiguous mu...
Vladimir Pavlovic, James M. Rehg, Ashutosh Garg, T...
— Map learning is a fundamental task in mobile robotics because maps are required for a series of high level applications. In this paper, we address the problem of building maps ...
Patrick Pfaff, Rudolph Triebel, Cyrill Stachniss, ...
The Aero Repair and Overhaul industry is facing an increasing challenge of prediction and scheduling of engine overhauls to remain competitive in a complex business arena. An appr...
Armin Stranjak, Partha Sarathi Dutta, Mark Ebden, ...