KSBT 2015 - Workshop on Knowledge, Skill, and Behavior Transfer in Autonomous Robots

AAAI-15 Workshop on
Knowledge, Skill, and Behavior Transfer in Autonomous Robots
http://www.cs.utexas.edu/~matteo/ksbt15
January 25?26, 2015, Austin, Texas, USA
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IMPORTANT DATES
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Paper submission: October 14, 2014
Notification of acceptance: November 14, 2014
Camera ready deadline: November 25, 2014
AAAI-15 Workshop Program: January 25?26, 2015
DESCRIPTION
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Autonomous robots have achieved high levels of performance and reliability at
specific tasks. However, for them to be practical and effective at everyday
tasks in our homes and offices, they must be able to learn to perform different
tasks over time, and rapidly adapt to new situations.
Learning each task in isolation is an expensive process, requiring large
amounts of both time and data. In robotics, this expensive learning process
also has secondary costs, such as energy usage and joint fatigue. Furthermore,
as robotic hardware evolves or new robots are acquired, these robots must be
trained, which is extremely inefficient if performed tabula rasa.
Recent developments in knowledge representation, machine learning, and optimal
control provide a potential solution to this problem, enabling robots to
minimize the time and cost of learning new tasks by building upon knowledge
acquired from other tasks or by other robots. This ability is essential to the
development of versatile autonomous robots that can perform a wide variety of
tasks and rapidly learn new abilities.
Various aspects of this problem have been addressed by different communities in
artificial intelligence and robotics. This workshop will seek to draw together
researchers from these different communities toward the goal of enabling
autonomous robots to support a wide variety of tasks, rapidly and robustly
learn new abilities, adapt quickly to changing contexts, and collaborate
effectively with other robots and humans.
TOPICS
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We are seeking broad participation from the areas including, but not limited
to:
- Transfer in Autonomous Robots: inter-task transfer learning, transfer over
long sequences of tasks, cross-domain transfer learning, long-term autonomy,
autonomy in dynamic and noisy environments, lifelong learning, knowledge
representation, transfer between simulated and real robots.
- Multi-Robot Systems: multi-robot knowledge transfer, task switching in
multi-robot learning, distributed transfer learning, knowledge/skill transfer
across heterogeneous robots.
- Human-Robot Interaction: human-robot knowledge/skill transfer, transfer in
mixed human-robot teams, learning by demonstration, imitation learning.
- Cloud Networked Robotics: access to shared knowledge, reasoning, and skills
in the cloud, cloud-based knowledge/skill transfer, cloud-based distributed
transfer learning.
- Applications: testbeds and environments, data sets, evaluation methodology.
SUBMISSIONS
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Contributions can be full-length papers (up to 7 pages), or extended
abstracts, and late breaking results (up to 2 pages). The papers follow the
same format as AAAI-15, in particular page 7 (for full papers) can contain
references only.
Submissions will be peer reviewed and evaluated on both their technical merit
along with their potential to generate discussion and promote collaboration
within the community.
Submission Website:
Authors should submit their contributions electronically in PDF (AAAI format)
through Easychair https://www.easychair.org/conferences/?conf=ksbt20... .