Editing Developmental robotics (section)

== Open questions ==

As developmental robotics is a relatively new research field and at the same time very ambitious, many fundamental open challenges remain to be solved.

First of all, existing techniques are far from allowing real-world high-dimensional robots to learn an open-ended repertoire of increasingly complex skills over a life-time period. High-dimensional continuous sensorimotor spaces constitute a significant obstacle to be solved. Lifelong [[cumulative learning]] is another one. Actually, no experiments lasting more than a few days have been set up so far, which contrasts severely with the time needed by human infants to learn basic sensorimotor skills while equipped with brains and morphologies which are tremendously more powerful than existing computational mechanisms.

Among the strategies to explore to progress towards this target, the interaction between the mechanisms and constraints described in the previous section shall be investigated more systematically. Indeed, they have so far mainly been studied in isolation. For example, the interaction of intrinsically motivated learning and socially guided learning, possibly constrained by maturation, is an essential issue to be investigated.

Another important challenge is to allow robots to perceive, interpret and leverage the diversity of [[Multimodal_interaction|multimodal]] social cues provided by non-engineer humans during human-robot interaction. These capacities are so far, mostly too limited to allow efficient general-purpose teaching from humans.

A fundamental scientific issue to be understood and resolved, which applied equally to human development, is how compositionality, functional hierarchies, primitives, and modularity, at all levels of sensorimotor and social structures, can be formed and leveraged during development. This is deeply linked with the problem of the emergence of symbols, sometimes referred to as the "[[symbol grounding problem]]" when it comes to language acquisition. Actually, the very existence and need for symbols in the brain are actively questioned, and alternative concepts, still allowing for compositionality and functional hierarchies are being investigated.

During biological epigenesis, morphology is not fixed but rather develops in constant interaction with the development of sensorimotor and social skills. The development of morphology poses obvious practical problems with robots, but it may be a crucial mechanism that should be further explored, at least in simulation, such as in morphogenetic robotics.

Another open problem is the understanding of the relation between the key phenomena investigated by developmental robotics (e.g., hierarchical and modular sensorimotor systems, intrinsic/extrinsic/social motivations, and open-ended learning) and the underlying brain mechanisms.

Similarly, in biology, developmental mechanisms (operating at the ontogenetic time scale) interact closely with evolutionary mechanisms (operating at the phylogenetic time scale) as shown in the flourishing "[[evo-devo]]" scientific literature.<ref name="Muller07">{{cite journal
| last1 = Müller | first1 = G. B. | date = 2007 | title = Evo-devo: extending the evolutionary synthesis | journal = Nature Reviews Genetics | volume = 8 | issue = 12 | pages = 943–949 | doi=10.1038/nrg2219 | pmid=17984972| s2cid = 19264907 }}</ref>
However, the interaction of those mechanisms in artificial organisms, developmental robots, in particular, is still vastly understudied. The interaction of evolutionary mechanisms, unfolding morphologies and developing sensorimotor and social skills will thus be a highly stimulating topic for the future of developmental robotics.