activity
20182026
most citedCurriculum Learning for Reinforcement Learning Domains: A Framework and Survey

229 citations · 329 across the 32 of their papers we have counts for

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Showing 2022Show all

5 papers · 1 filter

cs.RO2022★ 1 cited

Knowledge-driven Scene Priors for Semantic Audio-Visual Embodied Navigation

Gyan Tatiya, Jonathan Francis, Luca Bondi +4

Generalisation to unseen contexts remains a challenge for embodied navigation agents. In the context of semantic audio-visual navigation (SAVi) tasks, the notion of generalisation…

cs.RO2022★ 13 cited

Transferring Implicit Knowledge of Non-Visual Object Properties Across Heterogeneous Robot Morphologies

Gyan Tatiya, Jonathan Francis, Jivko Sinapov

Humans leverage multiple sensor modalities when interacting with objects and discovering their intrinsic properties. Using the visual modality alone is insufficient for deriving in…

cs.AI2022★ 1 cited

RAPid-Learn: A Framework for Learning to Recover for Handling Novelties in Open-World Environments

Shivam Goel, Yash Shukla, Vasanth Sarathy +2

We propose RAPid-Learn: Learning to Recover and Plan Again, a hybrid planning and learning method, to tackle the problem of adapting to sudden and unexpected changes in an agent's…

cs.AI2022★ 25 cited

Creative Problem Solving in Artificially Intelligent Agents: A Survey and Framework

Evana Gizzi, Lakshmi Nair, Sonia Chernova +1

Creative Problem Solving (CPS) is a sub-area within Artificial Intelligence (AI) that focuses on methods for solving off-nominal, or anomalous problems in autonomous systems. Despi…

cs.RO2022★ 4 cited

ACuTE: Automatic Curriculum Transfer from Simple to Complex Environments

Yash Shukla, Christopher Thierauf, Ramtin Hosseini +2

Despite recent advances in Reinforcement Learning (RL), many problems, especially real-world tasks, remain prohibitively expensive to learn. To address this issue, several lines of…