Conference proceeding
Teaching a Virtual Robot to Perform Tasks by Learning from Observation
UBIQUITOUS COMPUTING AND AMBIENT INTELLIGENCE: SENSING, PROCESSING, AND USING ENVIRONMENTAL INFORMATION, v 9454
01 Jan 2015
Abstract
We propose a methodology based on Learning from Observation in order to teach a virtual robot to perform its tasks. Our technique only assumes that behaviors to be cloned can be observed and represented using a finite alphabet of symbols. A virtual agent is used to generate training material, according to a range of strategies of gradually increasing complexity. We use Machine Learning techniques to learn new strategies by observing and thereafter imitating the actions performed by the agent. We perform several experiments to test our proposal. The analysis of those experiments suggests that probabilistic finite state machines could be a suitable tool for the problem of behavioral cloning. We believe that the given methodology is easy to integrate in the learning module of any Ubiquitous Robot Architecture.
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Details
- Title
- Teaching a Virtual Robot to Perform Tasks by Learning from Observation
- Creators
- Cristina Tirnauca - University of CantabriaJose L. Montana - University of CantabriaCarlos Ortiz-Sobremazas - Univ Cantabria, E-39005 Santander, SpainSantiago Ontanon - Drexel UniversityAvelino J. Gonzalez - University of Central Florida
- Contributors
- J M GarciaChamizo (Editor)G Fortino (Editor)S F Ochoa (Editor)
- Publication Details
- UBIQUITOUS COMPUTING AND AMBIENT INTELLIGENCE: SENSING, PROCESSING, AND USING ENVIRONMENTAL INFORMATION, v 9454
- Series
- Lecture Notes in Computer Science
- Publisher
- Springer Nature
- Number of pages
- 13
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Computer Science
- Web of Science ID
- WOS:000375991300010
- Scopus ID
- 2-s2.0-84952333272
- Other Identifier
- 991019167876604721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Computer Science, Artificial Intelligence
- Computer Science, Hardware & Architecture
- Computer Science, Information Systems
- Computer Science, Interdisciplinary Applications
- Computer Science, Theory & Methods