Cognitive Developmental Robotics Approach

Emergence of higher order cognitive functions through learning and development is one of the greatest challenges in trying to make artificial systems more intelligent since existing systems are of limited capability even in fixed environments. Related disciplines are not just AI and robotics but also neuroscience, cognitive science, developmental psychology, sociology, and so on, and we share this challenge. An obvious fact is that we have insufficient knowledge and too superficial implementations based on such knowledge to declare that we have only one unique solution to the mystery. The main reasons are:

  • There is little knowledge and few facts on the mechanism of higher order human cognitive functions, therefore, the artificial systems that aim at realizing such functions are based on the designers’ shallow understanding of them.
  • A more serious issue is how these functions are learned and/or developed from a viewpoint of design.
  • Further, is the current understanding and realization of the primary functions sufficient if we suppose that the higher order cognitive functions are acquired through the development process from these primary functions?

One possibility to answer these claims and questions is to discuss how higher order cognitive functions are acquired involving the context and dynamics of the whole system instead of separately realizing each higher order function as a single module. A promising approach is a synthetic one based on both the explanation theory and more importantly the design theory that is expected to fill in the gap between the existing disciplines instead of staying in one closed discipline, and to provide new understanding of human cognitive development.

A key idea is “physical embodiment” whose meaning has been frequently defined and argued already (ex., [18], [19], [20], [21], [22], [23], [24], [25]). Kuniyoshi [26] described it as follows:

“The agent’s physical body specifies the constraints on the interaction between the agent and its environment that generate the rich contents of its process or consequences. It also gives the meaningful structure to the interaction with environment, and is the physical infrastructure to form the cognition and action.”

The key concept of the above “physical embodiment” is shaped in the context of development as follows. At the early stage of human development (embryo, fetus, neonate, infant, and so on), interactions with various physical environments have a major role in determining the information structuring inside the individual such as body representation, motor image, and object permanency. On the other hand, at the later stage, social behaviors such as early communication, joint attention, imitation of various actions including vocalization, empathy, and verbal communication gradually emerged due to interac- tions with other agents. Regardless of the premature or mature state of the individual, the common aspect of these developmental processes is a sort of “scaffolding” by the environment including other agents that triggers the sensorimotor mapping and promotes the infants’ autonomy, adaptability, and sociality, directly or indirectly, and explicitly or implicitly.

A representative synthetic approach is cognitive developmental robotics (in short, CDR) [22]. Similar approaches can be found in [24] or [27], but CDR puts more emphasis on the human/humanoid cognitive development. A slightly different approach is taken by ATR team [28] who aims to program humanoid behavior through the observation and understanding of human behavior and vice versa. Though partially sharing the purpose of human understanding, they do not exactly deal with developmental aspect.

As mentioned above, the developmental process consists of two phases: the individual development at an early stage and the social development through interaction between individuals at a later stage. The former relates to mainly neuroscience (internal mechanism), and the latter to cognitive science and developmental psychology (behavior observation). Intrinsically, both should be seamless, but there is a big difference between them at the representation level for the research target to be understood. CDR aims not at simply filling the gap between them but more challengingly at building a new paradigm that provides new understanding of ourselves and at at the same time new design theory of humanoids symbiotic with us. So far, CDR has been mainly focusing on the computational model of cognitive development, but in order to more deeply understand how humans develop, robots can be used as new means as reliable reproduction tools in certain situations such as psychological experiments. The following is a summary:

  • A: construction of computational model of cognitive development:
    1. hypothesis generation: proposal of a computational model or hypothesis based on knowledge from existing disciplines
    2. computer simulation: simulation of the process difficult to implement with real robots such as physical body growth
    3. hypothesis verification with real agents (humans, animals, and robots), then go to 1.
  • B: offer new means or data to better understand human developmental process => mutual feedback with A:
    1. measurement of brain activity by imaging methods
    2. verification using human subjects or animal ones
    3. providing the robot as a reliable reproduction tool in (psychological) experiments.