Towards Representational Autonomy of Agents in Artificial Environments

Abstract

Abstract. Autonomy is a crucial property of an artificial agent. The type of representational structures and the role they play in the preservation of an agent's autonomy are pointed out. A framework of self-organised Peircean semiotic processes is introduced and it is then used to demonstrate the emergence of grounded representational structures in agents interacting with their environment. Autonomy and Representations in Strong AgencyThere is an interesting interdependence between the three fundamental properties of interactivity, intentionality and autonomy which are used to describe an agent. As it is suggested in [1], there is no function without autonomy, no intentionality without function and no meaning without intentionality. The circle closes by considering meaning (representational content) as a prerequisite for the maintenance of system's autonomy during its interaction. Moreover, the notion of representation is central to almost all theories of cognition, therefore being directly and indirectly connected with fundamental problems in the design of artificial cognitive agents [2], at the pure cognitivistic framework as much as at the embodied and dynamic approaches [3]. Although an embodied agent seems to be able to handle very simple tasks with only primitive stimulus-response actions, its cognitive capabilities cannot scale to tackle more complex phenomena. These and other problems are evidences that the use of representations, even in reflexive behaviors, becomes essential [4]. However, representations should not be generic, context-free and predetermined, but they should be an emergent product of the interaction between an agent and its environment [2]. Emergent Representations via Self-organised Semiotic ProcessesSelf-organised and embodied systems admit no functional usefulness to representations. Based on the abovementioned, the incorporation of a process to support the vehicle of the representation which carries internal information about an external state seems imperative. This process should give the interactive dimension to the self-organising system and furthermore, it should correspond to the embedded structure of emergent representations. Peircean semiosis [5] can be seen as the process which drives the system into meaningful interaction. In the proposed framework, intelligence is not considered as an extra module, but as an asset emerging from the agent's functionality for interaction and the aim is the unification of the modality of interaction, perception and action with the smallest possible number of representational primitives. The present attempt is in correspondence with contemporary works in AI, such as [6] and [7]. In the present paper, there is an attempt to design a more generic architecture which will integrate aspects of self-organisation and embodiment with Peircean semiotics. There is in no way a demonstration of a totally autonomous system, but the introduced architecture overcomes the symbol-grounding