decentralized manner. The use of an immunology based algorithm ushers a new era in ER wherein multiple subcontrollers can be created, evolved and arbitrated online in a collective of embodied robots.

Related Work
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Though a copious amount of research on ER can be cited, in this section we discuss the behaviour-decomposition and embodied evolution based techniques which are more pertinent to the work presented in this paper.\

Behavioural decomposition
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In this method, instead of just one robot controller, different subcontrollers are evolved to solve distinct subtasks. After these subcontrollers have adequately evolved, another (usually ANN based) controller is trained to map the input states of the robot to one of the already evolved subtask specific controllers. Lee [@lee1999evolving] describes each of the low-level subtask specific controllers as *behaviour primitives* while the top-level controller that has learned to map the inputs to these subcontrollers was termed the *behaviour arbitrator*.

Lee [@lee1999evolving] implemented a Genetic Programming (GP) based controller to solve a box-pushing task. This task was manually divided into two subtasks. Separate subcontrollers (primitives) were evolved for each subtask on a simulator. Finally, a GP based arbitrator was evolved to combine these subcontrollers hierarchically. Though their approach was implemented 