Gaudioso, G, Leonetti, M orcid.org/0000-0002-3831-2400 and Stone, P (2016) State Aggregation through Reasoning in Answer Set Programming. In: IJCAI Workshop on Autonomous Mobile Service Robots, 11 Jul 2016, New York, United States.
Abstract
For service robots gathering increasing amounts of information, the ability to realize which bits are rel- evant and which are not for each task is going to be crucial. Abstraction is, indeed, a fundamental characteristic of human intelligence, while it is still a challenge for AI. Abstraction through machine learning can inevitably only work in hindsight: the agent can infer whether some information was per- tinent from experience. However, service robots are required to be functional and effective quickly, and their users often cannot let the robot explore the environment long enough. We propose a method to perform state aggregation through reasoning in an- swer set programming, which allows the robot to determine if a piece of information is irrelevant for the task at hand before taking the first action. We demonstrate our method on a simulated mobile ser- vice robot, carrying out tasks in an office environ- ment.
Metadata
Item Type: | Conference or Workshop Item |
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Authors/Creators: |
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Keywords: | answer set programming; state abstraction; service robots; reinforcement learning |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) > Artificial Intelligence & Biological Systems (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 21 Jul 2016 09:28 |
Last Modified: | 28 Jul 2016 07:05 |
Status: | Published |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:102693 |