2 research outputs found
When the goal is to generate a series of activities: A self-organized simulated robot arm
Behavior is characterized by sequences of goal-oriented conducts, such as
food uptake, socializing and resting. Classically, one would define for each
task a corresponding satisfaction level, with the agent engaging, at a given
time, in the activity having the lowest satisfaction level. Alternatively, one
may consider that the agent follows the overarching objective to generate
sequences of distinct activities. To achieve a balanced distribution of
activities would then be the primary goal, and not to master a specific task.
In this setting, the agent would show two types of behaviors, task-oriented,
and task-searching phases, with the latter interseeding the former.
We study the emergence of autonomous task switching for the case of a
simulated robot arm. Grasping one of several moving objects corresponds in this
setting to a specific activity. Overall, the arm should follow a given object
temporarily and then move away, in order to search for a new target and
reengage. We show that this behavior can be generated robustly when modeling
the arm as an adaptive dynamical system. The dissipation function is in this
approach time dependent. The arm is in a dissipative state when searching for a
nearby object, dissipating energy on approach. Once close, the dissipation
function starts to increase, with the eventual sign change implying that the
arm will take up energy and wander off. The resulting explorative state ends
when the dissipation function becomes again negative and the arm selects a new
target. We believe that our approach may be generalized to generate
self-organized sequences of activities in general.Comment: 10 pages, 7 figure