A mechanism for planning ahead would appear to be essential to any creature with more than insect level intelligence. In this paper it is shown how planning, using full means-ends analysis, can be had while avoiding the so called symbol grounding problem. The key role of knowledge representation in intelligence has been acknowledged since at least the enlightenment, but the advent of the computer has made it possible to explore the limits of alternate schemes, and to explore the nature of (...) our everyday understanding of the world around us. In particular, artificial intelligence (AI) and robotics has forced a close examination, by people other than philosophers, of what it means to say for instance that "snow is white." One interpretation of the "new AI" is that it is questioning the need for representation altogether. Brooks and others have shown how a range of intelligent behaviors can be had without representation, and this paper goes one step further showing how intending to do things can be achieved without symbolic representation. The paper gives a concrete example of a mechanism in terms of robots that play soccer. It describes a belief, desire and intention (BDI) architecture that plans in terms of activities. The result is a situated agent that plans to do things with no more ontological commitment than the reactive systems Brooks described in his seminal paper, "Intelligence without Representation.". (shrink)

This article addresses issues in developing cognitive architectures--generic computational models of cognition. Cognitive architectures are believed to be essential in advancing understanding of the mind, and therefore, developing cognitive architectures is an extremely important enterprise in cognitive science. The article proposes a set of essential desiderata for developing cognitive architectures. It then moves on to discuss in detail some of these desiderata and their associated concepts and ideas relevant to developing better cognitive architectures. It argues for the importance of taking (...) into full consideration these desiderata in developing future architectures that are more cognitively and ecologically realistic. A brief and preliminary evaluation of existing cognitive architectures is attempted on the basis of these ideas. (shrink)

This paper explores an approach for autonomous generation of symbolic representations from an agent's subsymbolic activities within the agent-environment interaction. The paper describes a psychologically plausible general framework and its various methods for autonomously creating symbolic representations. The symbol generation is accomplished within, and is intrinsic to, a generic and comprehensive cognitive architecture for capturing a wide variety of psychological processes (namely, CLARION). This work points to ways of obtaining more psychologically/cognitively realistic symbolic and subsymbolic representations within the framework of (...) a cognitive architecture, and accentuates the relevance of such an approach to cognitive science and psychology. (shrink)

How to model meaning processes (semiosis) in artificial semiotic systems? Once all computer simulation becomes tantamount to theoretical simulation, involving epistemological metaphors of world versions, the selection and choice of models will dramatically compromise the nature of all work involving simulation. According to the pragmatic Peircean based approach, semiosis is an interpreter-dependent process that cannot be dissociated from the notion of a situated (and actively distributed) communicational agent. Our approach centers on the consideration of relevant properties and aspects of Peirce’s (...) pragmatic concept of semiotics. Upon developing this approach, we have no pretensions of our being able to present an exhaustive analysis of the differences between Peirce and other theoretical positions. Nevertheless, our contribution will serve to demonstrate how theorists contribute toward revealing certain fundamental ‘semiotic constraints’ that will be of interest and importance. (shrink)

This paper deals with the problem of understanding semiosis and meaning in cognitive systems. To this aim we argue for a unified two-factor account according to which both external and internal information are non-independent aspects of meaning, thus contributing as a whole in determining its nature. To overcome the difficulties stemming from this approach we put forward a theoretical scheme based on the definition of a suitable representation space endowed with a set of transformations, and we show how it can (...) be implemented, in the case of a single agent, by a neural network architecture. Numerical experiments conducted on different instances of the latter show that similar representations are developed as a consequence of the fact that these instances are facing a similar semantic task. This allows to model social and environmental influences through a system of interacting agents, each described by a specific implementation of this model architecture. (shrink)

The paper develops a new holistic theory of the word by integrating semiotic, linguistic, and psychological perspectives and introduces the Cogitative-Sensory Word Model, the CogSens Model, that unites the human mind and body. Saussure’s two-sided sign is replaced by a Peirce-inspired three-sided conception in which the expression unit mediates two content units, namely, an idea content connected to the human mind and an image content linked to the human body. It is argued that it is the word that makes human (...) language a unique tool of communication. Moreover, it is demonstrated how words interact with grammar to create an utterance. Finally, it is suggested that speech perception, i.e., fission of idea and image content, is the mirror image of speech production, i.e., fusion of idea and image content. (shrink)

Based on formal-theoretical principles about the sign processes involved, we have built synthetic experiments to investigate the emergence of communication based on symbols and indexes in a distributed system of sign users, following theoretical constraints from C.S.Peirce theory of signs, following a Synthetic Semiotics approach. In this paper, we summarize these computational experiments and results regarding associative learning processes of symbolic sign modality and cognitive conditions in an evolutionary process for the emergence of either symbol-based or index-based communication.

This article reviews eight proposed strategies for solving the Symbol Grounding Problem (SGP), which was given its classic formulation in Harnad (1990). After a concise introduction, we provide an analysis of the requirement that must be satisfied by any hypothesis seeking to solve the SGP, the zero semantical commitment condition. We then use it to assess the eight strategies, which are organised into three main approaches: representationalism, semi-representationalism and non-representationalism. The conclusion is that all the strategies are semantically committed and (...) hence that none of them provides a valid solution to the SGP, which remains an open problem. (shrink)