Active Improvement of Control Policies with Bayesian Gaussian Mixture Model
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The work of this thesis centers around the research subject of distributed robotic search. Within the field of distributed robotic systems, a task of particular interest is attempting to locate one or more targets in a possibly unknown environment. While n ...
As robots start pervading human environments, the need for new interfaces that would simplify human-robot interaction has become more pressing. Robot Programming by Demonstration (RbD) develops intuitive ways of programming robots, taking inspiration in st ...
Exploratory activities seem to be intrinsicallyrewarding for children and crucial for their cognitive development. Can a machine be endowed with such an intrinsic motivation system? This is the question we study in this paper, presenting a number of comput ...
Designing effective behavioral controllers for mobile robots can be difficult and tedious; this process can be circumvented by using unsupervised learning techniques which allow robots to evolve their own controllers online in an automated fashion. In mult ...
Designing effective behavioral controllers for mobile robots can be difficult and tedious; this process can be circumvented by using unsupervised learning techniques which allow robots to evolve their own controllers in an automated fashion. In multi-robot ...
Model-based synthesis of distributed controllers for multi-robot systems is commonly approached in either a top-down or bottom-up fashion. In this paper, we investigate the experimental challenges of both approaches, with a special emphasis on resource-con ...
Robot PbD started about 30 years ago, growing importantly during the past decade. The rationale for moving from purely preprogrammed robots to very flexible user-based interfaces for training the robot to perform a task is three-fold. First and foremost, P ...
We present a Programming by Demonstration (PbD) framework for generically extracting the relevant features of a given task and for addressing the problem of generalizing the acquired knowledge to different contexts. We validate the architecture through a s ...
Robot programming by demonstration (RPD) covers methods by which a robot learns new skills through human guidance. We present an interactive, multimodal RPD framework using active teaching methods that places the human teacher in the robot's learning loop. ...
Designing effective behavioral controllers for mobile robots can be difficult and tedious; this process can be circumvented by using online learning techniques which allow robots to generate their own controllers online in an automated fash- ion. In multi- ...