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Symbolic Representations
Synthesizing Navigation Abstractions for Planning with Portable Manipulation Skills
We address the problem of efficiently learning high-level abstractions for task-level robot planning. Existing approaches require large …
Eric Rosen
,
Steven James
,
Sergio Orozco
,
Vedant Gupta
,
Max Merlin
,
Stefanie Tellex
,
George Konidaris
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Automatic Encoding and Repair of Reactive High-Level Tasks with Learned Abstract Representations
We present a framework for the automatic encoding and repair of high-level tasks. Given a set of skills a robot can perform, our …
Adam Pacheck
,
Steven James
,
George Konidaris
,
Hadas Kress-Gazit
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Learning Abstract and Transferable Representations for Planning
We are concerned with the question of how an agent can acquire its own representations from sensory data. We restrict our focus to …
Steven James
,
Benjamin Rosman
,
George Konidaris
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Autonomous Learning of Object-Centric Abstractions for High-Level Planning
We propose a method for autonomously learning an object-centric representation of a continuous and high-dimensional environment that is …
Steven James
,
Benjamin Rosman
,
George Konidaris
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Learning Portable Representations for High-Level Planning
We present a framework for autonomously learning a portable representation that describes a collection of low-level continuous …
Steven James
,
Benjamin Rosman
,
George Konidaris
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Learning Object-Centric Representations for High-Level Planning in Minecraft
We propose a method for autonomously learning an object-centric representation of a highdimensional environment that is suitable for …
Steven James
,
Benjamin Rosman
,
George Konidaris
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Symbol Emergence in Cognitive Developmental Systems: A Survey
Humans use signs, e.g., sentences in a spoken language, for communication and thought. Hence, symbol systems like language are crucial …
Tadahiro Taniguchi
,
Emre Ugur
,
Matej Hoffmann
,
Lorenzo Jamone
,
Takayuki Nagai
,
Benjamin Rosman
,
Toshihiko Matsuka
,
Naoto Iwahashi
,
Erhan Oztop
,
Justus Piater
,
Florentin Wörgötter
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Learning to Plan with Portable Symbols
We present a framework for autonomously learning a portable symbolic representation that describes a collection of low-level continuous …
Steven James
,
Benjamin Rosman
,
George Konidaris
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