ICRA 2014 Workshop: General Intelligence for Humanoid Robots


Workshop on General Intelligence for Humanoid Robots

a workshop affiliated with

ICRA 2014, Hong Kong, May 31 – June 5, 2014

 

This workshop is completed, but this page is left online to serve as a reference point for related materials.

The papers presented at the workshop are available at icra_humanoid_session_v4.

Videos of 5 of the talks presented at the workshop are on YouTube — including the discussions, which were quite interesting!

THEME

The intersection of humanoid robotics and Artificial General Intelligence research is both obvious and extensive. To create mobile robots, active in everyday human environments, able to carry out a variety of goals in a flexible way, requires one to make a fair degree of headway toward the broader problem of Artificial General Intelligence. The intersection between robotics and AGI is particularly important where humanoid robotics are concerned, as people naturally expect the humanoid robots they interact with to display a certain level human-like savvy. The humanoid form factor also presents unique opportunities for learning intelligent behaviors via emotionally rich interactions with humans. The workshop will focus on the full breadth of issues at the intersection of humanoid robotics and Artificial General Intelligence. In other words, it will focus on

  • the use of artificial general intelligence oriented software and hardware to cope with the challenges involved in achieving goals involving controlling humanoid bodies in the everyday world
  • the design of humanoid bodies capable of serving as appropriate vehicles for artificial general intelligence technology

The workshop is open to contributions on any topic directly related to the interfacing between artificial general intelligence architectures and the problem of controlling humanoid robot bodies in the everyday human world. Contributions presenting empirical or mathematical results will be very welcome; contributions describing new approaches at an earlier stage of development will also be accepted in some cases, if the ideas are novel and clearly presented and argued for. Specific topics of interest include (but are definitely not limited to):

  • Analog hardware for adaptive control and perceptual-motor integration
  • Autonomy: the capabilities of a generally intelligent robot to find itself its own motivations and goals.
  • Emotional intelligence: use of emotional expression and understanding to help a robotic system learn and understand better
  • Entity identification: Identification of which groups of percepts or atomic objects in a world are sensibly grouped together as a coherent “entity”
  • Event identification: Identification of which groups of temporal happenings in a world are sensibly grouped together as a coherent “event”
  • Generally-intelligent adaptive control: Learning patterns of actuator control in a manner that displays strong adaptiveness, i.e. ability to learn to carry out actions qualitatively different from those for which a system was previously trained or programmed. E.g. a robot with the ability to learn to walk on different kinds of terrain via adapting to its experience.
  • Generally-intelligent adaptive perception: Perception of objects and events in a world, in a manner that displays strong adaptiveness, i.e. ability to perceive objects and events qualitatively different from those for which a
  • Modeling of other Agents: modeling of other agents, in terms of their likely behaviors in various contexts in the world
  • Self-modeling: Building a model of the agent’s mental and physical self based on the agent’s observations of its own interactions in the world
  • Sensorimotor integration: methodologies for linking perception with action in a robotically embodied AGI.
  • Spatial, temporal and spatiotemporal reasoning: Inference about objects and events in a world, in a manner that takes careful account of the spatial and temporal relationships between them
  • Symbol grounding: Learning of groundings for words and/or syntactic and/or semantic relationships, via experience interacting with objects and entities in a world
  • Theory of mind: modeling of other agents, in terms of the knowledge and beliefs on which their actions are based

 

KEYNOTES

  • Ben Goertzel, OpenCog Project: Using Robots and Virtual Worlds Together to Advance General Intelligence
  • David Hanson, Hanson Robotics (creator of Robot Einstein):  The Need for Creativity, Aesthetics, and the Arts in the Design of Increasingly Intelligent Humanoid Robots
  • Mark Sagar, director of the Laboratory for Animate Technologies based at the Auckland Bioengineering Institute: Baby X: Building a Biomimetic Virtual Infant
  • Mark Tilden, creator of RoboSapien and BEAM robotics: An Applied Example of Analog Biomorphic Robot Design 

PAPER SUBMISSION DETAILS

The workshop proceedings will be published within the ICRA14 Workshop/Tutorial CDROM and electronically as a pdf file. Format for submissions: Papers should be prepared according to the ICRA14 final camera ready format and should be 4 to 6 pages long. The detailed information on the paper format is available from the ICRA14 page. http://www6.cityu.edu.hk/icra2014/paper_submission.htm. Papers should be sent to David Hanson by email at david@hansonrobotics.com. Important dates

  • Deadline for Paper submission: April 1, 2014
  • Acceptance with review comments: April 5, 2014
  • Deadline for final paper submission: April 10, 2014

WORKSHOP ORGANIZATION

The workshop chairs are:

  • Dr. Ben Goertzel, Novamente LLC and Hong Kong Polytechnic University
  • Dr. David Hanson, Hanson Robotics
  • Dr. Mark Tilden, creator of RoboSapien & inventor of BEAM robotics
  • Dr. Gino Yu, leader of robotics & AI projects at Hong Kong Poly U

The workshop organizing committee comprises leading researchers with expertise in humanoid robotics, cognitive robotics and AGI.

  • Itamar Arel, University of Tennessee, Knoxville TN, USA
  • Joscha Bach, Humboldt University, Germany
  • Yoseph Bar-Cohen, Jet Propulsion Laboratory, USA
  • Cindy Bethel, Mississippi State U., USA
  • Antonio Chella, University of Palermo, Italy
  • Danilo De Rossi, Centro “E. Piaggio”, Italy
  • Marc-Olivier Gewaltig, EPFL – Blue Brain Project, Switzerland
  • David Hanson, Hanson Robotics, Austin TX, USA
  • Johan Hoorn, VU Amsterdam, Netherlands
  • Matthew Ikle’, Adams State College, USA
  • Dan Popa, University of Texas, Arlington TX, USA
  • Stephen Reed, TexAI, Austin TX, USA
  • Brandon Rohrer, Sandia Labs, New Mexico, USA
  • Mark Sagar, University of Auckland, NZ
  • Pei Wang, Temple University, Philadelphia, USA