Learning and Measuring Specialization in Collaborative Swarm Systems
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We propose a multi-robot tracking method to provide state estimates that allow a group of robots to maintain a formation even when the communication fails. We extend a Gaussian Mixture Probability Hypothesis Density filter to incorporate, firstly, absolute ...
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Computational education offers an important add-on to conventional teaching. To provide optimal learning conditions, accurate representation of students' current skills and adaptation to newly acquired knowledge are essential. To obtain sufficient represen ...
The two-pass information bottleneck (TPIB) based speaker diarization system operates independently on different conversational recordings. TPIB system does not consider previously learned speaker discriminative information while di-arizing new conversation ...
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A long standing goal in artificial intelligence is to make robots seamlessly interact with humans in performing everyday manipulation skills. Learning from demonstrations or imitation learning provides a promising route to bridge this gap. In contrast to d ...
This report presents key interdisciplinary insights from IRGC’s expert workshop on the governance of decision-making algorithms, with particular focus on automated decisions based on learning algorithms (DMLAs). It highlights, among others, the need to imp ...
Performing remote manipulation tasks by teleoperation with limited bandwidth, communication delays and environmental differences is a challenging problem. In this paper, we learn a task-parameterized generative model from the teleoperator demonstrations us ...
This paper describes the design of a robot agent and associated learning algorithms to help children in handwriting acquisition. The main issue lies in how to program a robot to obtain human-like handwriting and then exploit it to teach children. We propos ...