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Effect regulated projection of robot’s action space for production and prediction of manipulation primitives through learning progress and predictability based exploration
(IEEE, 2021-06)
In this study, we propose an effective action parameter exploration mechanism that enables efficient discovery of robot actions through interacting with objects in a simulated table-top environment. For this, the robot ...
Inferring cost functions using reward parameter search and policy gradient reinforcement learning
(IEEE, 2021)
This study focuses on inferring cost functions of obtained movement data using reward parameter search and policy gradient based Reinforcement Learning (RL). The behavior data for this task is obtained through a series of ...
Imitation and mirror systems in robots through Deep Modality Blending Networks
(Elsevier, 2022-02)
Learning to interact with the environment not only empowers the agent with manipulation capability but also generates information to facilitate building of action understanding and imitation capabilities. This seems to be ...
Deepsym: Deep symbol generation and rule learning for planning from unsupervised robot interaction
(AI Access Foundation, 2022)
Symbolic planning and reasoning are powerful tools for robots tackling complex tasks. However, the need to manually design the symbols restrict their applicability, especially for robots that are expected to act in open-ended ...
Developmental scaffolding with large language models
(IEEE, 2023)
Exploration and self-observation are key mechanisms of infant sensorimotor development. These processes are further guided by parental scaffolding to accelerate skill and knowledge acquisition. In developmental robotics, ...
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