1. A method for predicting a fall of a robot having at least two legs, the method comprising: receiving a learned representation generated by a supervised learning algorithm, the learned representation taking as inputs a plurality of features of a robot, the learned representation having as an output a classification comprising an indication of a balanced state or a falling state; determining a plurality of features of a current state of the robot, the determining based at least in part on a current value of a joint angle or joint velocity of the robot; and classifying the current state of the robot as being either balanced or falling, the classifying performed by evaluating the learned representation with the plurality of features of the current state of the robot.