Embodied AI

  • Investigator: Harold Soh. This work focuses on learning useful and robust deep world models using multiple, possibly unreliable, sensors. We find that current methods do not sufficiently encourage a shared representation …

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  • Investigator: Harold Soh. The principal aim of this project is to develop core techniques for learning models of other (human) agents: Artificial Theories of Mind and Body (AToM/B). We intend to …

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  • Tactile Learning & Perception

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    Investigator: Harold Soh The ability of humans to navigate our environment is heavily dependent on the quality and speed of sensing. Tactile sensing, or the sensation of touch and pressure, is …

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  • Investigator: Leong Tze Yun How can an AI agent focus attention in a complex, unknown environment for decision making? We investigate the use of context-sensitive transfer learning in hierarchical reinforcement learning. …

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