RepLearn 2013

RepLearn 2013
Workshop on Learning Rich Representations from Low-Level Sensors

July 2013 15

AAAI 2013

Monday, July 15th, 2013 in Bellevue, Washington, USA.
In conjunction with AAAI 2013.

Motivation and Relevance

A human-level artificially intelligent agent must be able to represent and reason about the world, at some level, in terms of high-level concepts such as entities and relations. The problem of acquiring these rich high-level representations, known as the knowledge acquisition bottleneck, has long been an obstacle for achieving human-level AI. A popular approach to this problem is to handcraft these high-level representations, but this has had limited success. An alternate approach is for rich representations to be learned autonomously from low-level sensor data. Potentially, the latter approach may yield more robust representations, and should rely less on human knowledge-engineering.

Topics

We are interested in all parts of the bridge between low-level-sensors and rich high-level representations and their use in reasoning tasks. This includes but is not limited to:

  • Learning concept hierarchies from sensor data.
  • Representing and learning invariant concepts.
  • Postulating objects and theoretical entities.
  • Postulating relations from sensor data, when the data is not explicitly relational.
  • Learning symbolic representations from numerical sensor data.
  • High-level reasoning grounded in robotic sensors and effectors.
  • Sensor-grounded research on cognitive architectures.

    • Invited Speakers

    Format

    This one-day workshop will begin with an explanation of the workshop's focus and research overview. We will decompose the workshop into themes that concern learning rich representations from sensor data: tasks, techniques, evaluations, or demonstrations. We will include invited talks from senior researchers who can summarize their long-term research on this topic. We will also include one or more panels that focus on the themes listed above, and their challenges.

     

    Important Dates

    • Paper submission:April 8th, 2013
    • Notification of acceptance: April 23rd, 2013
    • Camera-ready papers: May 9th, 2013
    • Early registration: May 17th, 2013
    • Workshop date: July 15th, 2013

    Workshop participants may also want to attend Yoshua Bengio's Deep Learning Tutorial the day before the workshop.

    Submission

    Submission is now closed. Camera-ready copies may be updated on EasyChair.

    Organizing Committee

    Program Committee