TESIS DOCTORAL - Robotics Lab - Universidad Carlos III de Madrid

1.1. Motivation 5Figure 1.2 depicts robots from all these levels placed according to their autonomy andthe importance of humans in their control. As shown, the higher level of autonomy, the lessimportant the role of the human is. This could clearly rises legal risks in case of malfunctionof the robot: who is responsible for that? [32].Figure 1.2: Levels of autonomy in robots in relation to the level of human controlBellman [28] states that autonomy implies a decision making process and this requiressome knowledge about the current state of the agent and environment, including its objectives.In consequence, the level of autonomy relates to the amount of decisional mechanismsthey are endowed with [33]. Moreover, several authors such as Arkin [34], Gadanho[24], Bellman [28], or Cañamero[29], in general, state that an autonomous agent must beself-sustained, which implies a decision making system. According to Hardy-Vallée [35],making choices is a reasoning process and rational decisions are made taking into accountthe probability and the outcomes of each action.Moreover, some definitions of robots classify them as a special kind of agents and,being an agent entails making choices [35]. Consequently, robots have to be endowedwith some kind of decision making mechanism. An autonomous robot acts on the basisof its own decisions [36] in order to fulfill its goals. Thus, it must know what action toexecute in every situation. In the case that this robot does not have this knowledge, it mustlearn this relation between situations and actions. According to Mataric [37], learninghas been denominated as one of the distinctive marks of the intelligence and introducingadaptation and learning skills in artificial systems is one of the greatest challenges of theartificial intelligence. Moreover, Gadanho [24] states that learning is an important skill foran autonomous agent, since it gives the agent the plasticity needed for being independent.