  Taking inspiration from the hypothesis of muscle synergies, we propose a
method to generate open loop controllers for an agent solving point-to-point
reaching tasks. The controller output is defined as a linear combination of a
small set of predefined actuations, termed synergies. The method can be
interpreted from a developmental perspective, since it allows the agent to
autonomously synthesize and adapt an effective set of synergies to new
behavioral needs. This scheme greatly reduces the dimensionality of the control
problem, while keeping a good performance level. The framework is evaluated in
a planar kinematic chain, and the quality of the solutions is quantified in
several scenarios.
