Intrinsic motivation without the need of defining an external reward has long been proposed for equipping artificial agents with behaviour previously only ...

Unsupervised Control : Efficient Inference for Time Series Modelling and Intrinsic Motivation · Angaben zum Objekt · Klassifikation und Themen · Beteiligte, Orts- ...

Unsupervised Control: Efficient Inference for Time Series Modelling and Intrinsic Motivation.PhD Thesis 2020. paper. [j1]. Q2. Maximilian Karl, Lasse H. E. ...

Nov 21, 2024 · We introduce a methodology for efficiently computing a lower bound to empowerment, allowing it to be used as an unsupervised cost function for ...

Reinforcement learning (RL) aims at au- tonomously performing complex tasks. To this end, a reward signal is used to steer the learning process.

Sep 10, 2024 · We introduce a methodology for efficiently computing a lower bound to empowerment, allowing it to be used as an unsupervised cost function ...

Jan 1, 2025 · Moreover, our method is computationally efficient and does not require editing the training data or retraining the model, and is therefore well ...

Aug 29, 2024 · In this study, we investigate an information-theoretic approach to intrinsic motivation, based on maximizing an agent's empowerment.

Nov 14, 2023 · This unified approach facilitates efficient intrinsic control combined with model learning. In this paper, we present a comprehensive intrinsic ...

Oct 13, 2023 · Unsupervised learning means analyzing the structure of a dataset without any other information than the data points themselves—in particular ...