1. Results – 100 Independent Trials Results – Single Trial
Morphological Scaffolding: How Evolution and Development Improve Robot Behavior Generation
Josh Bongard
Morphology, Evolution and Cognition Laboratory
Department of Computer Science, University of Vermont
Summary
Methods
Observation: Scaffolding — initially easing agents’ task environment, and then gradually making it more challenging as the agents learn — has been shown to increase the probability of evolving an agent capable of eventually succeeding in the challenging task environment.
Hypothesis: Rather than scaffolding the environment, can an agent’s own body provide a learning gradient?
Approach: Allow a legged robot to gradually change its body from a prone stance (lying flat on the ground, legs horizontal) to an upright stance (legs vertical). As evolution proceeds, remove this stance change so that later robots begin and end with an upright stance. Does changing the robot’s stance speed the discovery of a walking gait for the robot when upright?
Result: Allowing the robot’s body plan to change does increase the probability of eventually evolving a completely upright robot, but only if the body changes over both the evolutionary time scale and over the robot’s lifetime. This requires that the robot’s body change while it behaves.
Conclusion: In order to evolve robots capable of non-trivial behavior, it is necessary to allow the robot’s body to change over both phylogenetic and ontogenetic time scales.
Six sets of independent trials were conducted.
NS: No Scaffolding; throughout the evolutionary trial, each robot starts and ends with an upright stance.
BS: Between Scaffolding; once a robot evolves to reach the target, the robots’ beginning and ending stances are changed.
WS1-WS4: Within Scaffolding; each robot’s stance changes while it behaves; the initial and ending stances also change over evolutionary time.
Results – 100 Independent Trials
Results – Single Trial
(a)
(b)
(c)
Six x 100 independent trials
were conducted in which the
target object was placed in
front of the robot (a), 22.5o forward and to the left of the robot (b), and 45o forward and to the left of the robot (c; see images to the left).
Typical result when Within Scaffolding (WS1) is used.
Left column: A successful robot is evolved that begins and ends with a prone stance (WS1, f)
Middle column: This robot eventually produces a descendent that is also successful, but begins with a prone stance and ends with an upright stance.
Right column: This robot in turn produces a descendent that starts and ends with the upright stance, and successfully reaches the target object.
(a,b): When the robot must evolve to walk forward or only slightly to the left, there is no advantage to changing the robot’s body plan during evolution. (c): When the robot must walk and turn, there is no advantage to changing the robot’s body plan between evaluations (medium gray bars), but there is a significant advantage if the robot’s body is changed while it behaves (dark gray bars).