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, May 30, 2012

Ernest 11.3 in e-puck

Ernest 11.3 is an adaptation of Ernest 11.2 for the e-puck robot.

This video shows the e-puck robot in the "Box Environment" (left). The possibilities of interaction and the LED signals are the same as with Ernest 7 in e-puck.

The top-right part of the video shows the sequential trace with the same symbols as previously.

The bottom-center shows the new spatial memory (in an egocentric referential with the robot's front oriented towards the right). When Ernest enacts an interaction, the area that is concerned by this interaction is marked by a halo in spatial memory. Interactions that concern empty places are in white, interactions that concern walls are in green. The superimposition of different interactions in the same spatial location reveals occurrences of empty place phenomena (white halos) and wall phenomena (green halos).

Note that wrong associations can occur due to false detections. For example: false detection of a wall on the left on steps 221 and 222 (time 2:23). (We turned on additional light to provoke more false detections from step 100, time 0:59.)

The bottom-right part of the video represents coefficients of spatial overlapping between interactions (red segments). The more consistent the overlapping, the shorter the segment. Over time, interactions that concern the same kind of phenomena become grouped together because they consistently overlap. Two bundles of interactions emerge: white interactions form a bundle that represents empty places, green interactions form a bundle that represents walls.

On step 229, the false detection made on step 221 and 222 yields to a wrong association between the two bundles (mixed white and green halo in the center of spatial memory on time 2:25, and long red segment between the two bundles). This wrong association, however, does not impact Ernest's behavior too much because it remains weak.

This experiment demonstrates that Ernest 11.3 handles the imprecision in the robot’s displacements and in the sensors by keeping track of probabilities of presence of phenomena in Ernest's surrounding space. Simultaneously, Ernest gradually learns the notions of empty space phenomenon and wall phenomenon by associating the interactions that they afford. In turn, the recognition of phenomena helps Ernest organize its behavior by prompting interactions adapted to the phenomena that surround him.

Thursday, May 24, 2012

A Challenge for Emergent Cognition

The Small Loop Problem: A challenge for artificial emergent cognition. Olivier L. Georgeon, James B. Marshall. In proceedings of BICA2012, Annual Conference on Biologically Inspired Cognitive Architectures. Palermo, Italy, pp. 137-144. (October 31, 2012).

This paper presents the Small Loop Problem and how Ernest 11.2 handles it.