Olivier Georgeon's research blog—also known as the story of little Ernest, the developmental agent.

Keywords: situated cognition, constructivist learning, intrinsic motivation, bottom-up self-programming, individuation, theory of enaction, developmental learning, artificial sense-making, biologically inspired cognitive architectures, agnostic agents (without ontological assumptions about the environment).

Wednesday, April 25, 2012

Ernest 7 in e-puck

Here is Ernest 7 in an e-puck robot.

We implemented "touch" with the infrared sensors available on the front, left, and right side of the robot. The range of these sensors was set to approximately 5cm. When Ernest "touches", the corresponding led flashes. When the touching detects a wall, the two additional leds on the rear flash. When it bumps into a wall, all the leds flash.The symbols in the trace are the same as previously.

This video shows that Ernest learns to touch ahead before moving forward to avoid bumping, and learns to turn when it reaches a wall.

Tuesday, April 24, 2012

Ernest 11.2 in the Small Loop Problem


This video shows Ernest 11.2's temporal memory (up-left) and spatial memory (right) in the Small Loop Problem (bottom-left).

Like Ernest 11.1, Ernest 11.2 keeps track of interactions in his spatial memory. Touch interactions are represented by squares, move by white triangles, bump by red triangles, turn by half-circles.

Interactions that are enacted at the same spatial place are bundled together to represent the phenomenon that afforded them. The Small Loop Problem offers two kinds of phenomena: empty squares and walls. In temporal memory, the construction of bundles is represented by gray rounded rectangles (upper part). In spatial memory, bundles are represented by gray circles that contain interactions. These circles are fading to represent spatial memory decay.

For example, on step 13, Ernest bundles together the interactions touch front wall and bump. On step 19, the fact that Ernest touches a wall activates the still-partial wall bundle in front of Ernest (right side of spatial memory). This activation reminded Ernest that moving forward would cause bumping, which made him refrain from trying to move forward.

Ernest 11.2's spatial mechanism helps him perform better than Ernest 7 in the Small Loop Problem. Ernest 11.2 does not, however, constitute a full solution to the Small Loop Problem because he has pre-implemented knowledge. The position of interactions relatively to Ernest's body were hard-wired in spatial memory. Additionally, the consequences that certain interactions have on spatial memory were pre-implemented: move translates spatial memory and turn rotates spatial memory. A full solution to the Small Loop Problem must eliminate such pre-implemented assumptions.

Tuesday, April 10, 2012

Designing Environment-Agnostic Agents

Designing Environment-Agnostic Agents. Olivier L. Georgeon, Ilias Sakellariou. In proceedings of ALA2012, Adaptive Learning Agents workshop, at  AAMAS 2012, 11th International Conference on Autonomous Agents and Multiagent Systems. 25-32. (June 4-5th 2012).

In this paper, we define the notion of environment-agnostic agents. We also presents Ernest in NetLogo.