This article addresses a classical question: Can a machine use language meaningfully and if so, how can this be achieved? The first part of the paper is mainly philosophical. Since meaning implies intentionality on the part of the language user, artificial systems which obviously lack intentionality will be `meaningless'. There is, however, no good reason to assume that intentionality is an exclusively biological property and thus a robot with bodily structures, interaction patterns and development similar to those of human beings (...) would constitute a system possibly capable of meaning – a conjecture supported through a Wittgenstein-inspired thought experiment. The second part of the paper focuses on the empirical and constructive questions. Departing from the principle of epigenesis stating that during every state of development new structure arises on the basis of existing structure plus various sorts of interaction, a model of human cognitive and linguistic development is proposed according to which physical, social and linguistic interactions between the individual and the environment have their respective peaks in three consecutive stages of development: episodic, mimetic and symbolic. The transitions between these stages are qualitative, and bear a similarity to the stages in phylogenesis proposed by Donald and Deacon. Following the principle of epigenetic development, robotogenesis could possibly recapitulate ontogenesis, leading to the emergence of intentionality, consciousness and meaning. (shrink)

Connectionism seems to avoid many of the problems of classical artificial intelligence, but has it avoided all of them? In this thesis I examine the problem that Intentionality, the directedness of thought to an object, raises for connectionism. As a preliminary approach, I consider the role of Intentionality in classical artificial intelligence from the programmer’s point of view. In this investigation, one problem I identify with classical artificial intelligence is that the Intentionality of the programmer seems to be projected onto (...) the system, rather than the programmer creating a system whereby Intentionality arises intrinsically within the system. -/- In considering the current practice of connectionism, the same problem with Intentionality reappears. The assignment of Intentional content to input or output nodes in a neural network likewise projects the Intentionality of the programmer onto the system, and that projection is often reinforced by the training process of the neural network. However, connectionism seems to have an advantage over classical artificial intelligence in this respect, in that there is a form of neural network in which the network itself organizes the output nodes. The challenge is to utilize these self-organizing networks without having the programmer project Intentionality onto the system in an act of interpretation. -/- I suggest that the way to overcome these problems in connectionism is to embody the neural network within a world, whether physical or virtual, and to allow the system to develop concepts purely empirically. In this manner, connectionism can make scientific observations concerning the nature of cognition without the risk of contamination from the programmer’s own Intentionality. (shrink)