Web17 de mar. de 2024 · This collection refers to Awesome-Imitation-Learning and also contains our collected papers. To be precise, the "imitation learning" is the general problem of learning from expert demonstration (LfD). There are 2 names derived from such a description, which are Imitation Learning and Apprenticeship Learning due to historical … Web1 de mar. de 2024 · Hierarchical imitation learning with high and low level policies is investigated in recent work [7], [8]. These methods require ground-truth labeling of each sub-task to train the high-level ...
Hierarchical Few-Shot Imitation with Skill Transition Models
Web[NEW] Depuis 2024, je suis Data Scientist Ph.D confirmé au sein de l'équipe d'expertise NLP de Quantmetry. [OLD] Je suis doctorant en contrat CIFRE (convention industrielle de formation par la recherche) avec Orange Labs et l'Université d'Avignon (dans l'équipe du laboratoire académique LIA). Le sujet de ma thèse est "Apprentissage par … WebWe propose an algorithmic framework, called hierarchical guidance, that leverages the hierarchical structure of the underlying problem to integrate different modes of expert … sonya heitshusen whotv
Hierarchical Few-Shot Imitation with Skill Transition Models
Web14 de dez. de 2024 · Humans can leverage hierarchical structures to split a task into sub-tasks and solve problems efficiently. Both imitation and reinforcement learning or a combination of them with hierarchical structures have been proven to be an efficient way for robots to learn complex tasks with sparse rewards. However, in the previous work of … Web18 de out. de 2024 · We demonstrate the first large-scale application of model-based generative adversarial imitation learning (MGAIL) to the task of dense urban self … Web19 de jul. de 2024 · 3.2 Hierarchical Few-Shot Imitation with Skill T ransition Models Our method, shown in Fig. 2 , has three components: (i) Skill extraction, (ii) Skill adaptation via sony alarm clock setting time