• RL makes a robot's behaviour more adaptable (learn)

• RL implemented in a MA environment = more adaptable, robust, dynamically reconfigurable architecture

• Experimental results show RL can learn efficient control policies in a range of environments of varying complexity

• Experimental results shown RL provides a more efficient + safer method for guiding a robot back to a recharging station than a simple non-AI method