Special Issue on Symbol Grounding

Abstract

How can we achieve artificial systems that are capable of understanding human language? This question has been addressed by the field of artificial intelligence for decades and has undergone several paradigm shifts from rule-based approaches, proposing sets of symbolic rules to process language input to produce an intelligent behavior, to the insight that symbolic rules are not sufficient to deal with new situations, let alone new symbols, that have not been encountered before. Rather, it has been proposed that the symbols of a language need to be grounded in perception in order to allow for generalisation to new situations. This new formulation of the problem has been termed “Symbol Grounding” and proposes that any system capable of understanding symbols needs to be embodied in the sense that it has to be able to perceive its environment and to produce actions within this environment that cause significant changes and that these percepts and actions need to be tied to symbols that allow to abstract and thus to transfer knowledge. Research thus focuses either on simulated embodied agents or robots that are situated in a physical environment. Given the complex nature of the challenge, a range of different strands of research has emerged from which we tried to capture the most relevant ones in this Special Issue. Focusing on the development of grounding capabilities in infants brings in new perspectives and has, for example, lead to the insight that while the learning system has to be extremely adaptive to the environment, the social environment itself also adapts to the learner. In the contribution by Paul Vogt & J. Douglas Mastin it is thus discussed which aspects of such interactions should be modelled in artificial systems with a special focus on data “from the wild”.