The symbol grounding problem

Abstract

There has been much discussion recently about the scope and limits of purely symbolic models of the mind and abotlt the proper role of connectionism in cognitive modeling. This paper describes the "symbol grounding problem": How can the semantic interpretation of a formal symbol system be made intrinsic to the system, rather than just parasitic on the meanings in our heads? How can the meanings of the meaningless symbol tokens, manipulated solely on the basis of their (arbitrary) shapes, be grounded in anything but other meaningless symbols? The problem is analogous to trying to learn Chinese from a Chinese/Chinese dictionary alone. A candidate solution is sketched: Symbolic representations must be grounded bottom-up in nonsymbolic representations of two kinds: (1) iconic representations, which are analogs of the proximal sensory projections of distal objects and events, and (2) categorical representations, which are learned and innate feature detectors that pick out the invariant features of object and event categories from their sensory projections. Elementary symbols are the names of these object and event categories, assigned on the basis of their (nonsymbolic) categorical representations. Higher-order (3) symbolic representations, grounded in these elementary symbols, consist of symbol strings describing category membership relations (e.g. "An X is a Y that is Z ").Connectionism is one natural candidate for the mechanism that learns the invariant features underlying categorical representations, thereby connecting names to the proximal projections of the distal objects they stand for. In this way connectionism can be seen as a complementary component in a hybrid nonsymbolic/symbolic model of the mind, rather than a rival to purely symbolic modeling. Such a hybrid model would not have an autonomous symbolic "module," however; the symbolic functions would emerge as an intrinsically "dedicated" symbol system as a consequence of the bottom-up grounding of categories' names in their sensory representations. Symbol manipulation would be governed not just by the arbitrary shapes of the symbol tokens, but by the nonarbitrary shapes of the icons and category invariants in which they are grounded.

Emergence of communication and language in evolving robots

“…Overall, this implies that signal and meaning are not grounded (Harnad 1990) directly in sensorimotor states but rather in behaviors that are ultimately grounded in sensorimotor states.…”

Finding Your Way from the Bed to the Kitchen: Reenacting and Recombining Sensorimotor Episodes Learned from Human Demonstration

“…While clearly humans experience some kind of "inner world, " i.e., the ability to imagine their environment and their own interactions with it embodied/situated theories of cognition [e.g., Varela et al (1991), Clancey (1997), Clark (1997), and Lakoff and Johnson (1999)] have questioned the traditional view of symbolic mental representations. In artificial intelligence research, in particular, some have argued for the need of "symbol grounding" (Harnad, 1990), i.e., the grounding of amodal symbolic representations in non-symbolic iconic and categorical representations that allow to connect senses to symbols, while others have argued that the "physical grounding" of "embodied" and "situated" robots simply makes representation unnecessary [e.g., Brooks (1991)]. In this context, alternative accounts of cognition as based on different types of mental simulation or emulation have gained substantial interest [e.g., Barsalou (1999), Hesslow (2002), Grush (2004), Gallese (2005), and ].…”

How to make an autonomous robot as a partner with humans: design approach versus emergent approach

“…Many philosophical discussions have been forwarded, but it does not mean a solved problem yet. The physical symbol grounding problem especially, as proposed by Harnard (1990), delineates the difficulty regarding the meanings of the symbols themselves.…”