Cognitive Architectures and Autonomy: A Comparative Review

Abstract

One of the original goals of artificial intelligence (AI) research was to create machines with very general cognitive capabilities and a relatively high level of autonomy. It has taken the field longer than many had expected to achieve even a fraction of this goal; the community has focused on building specific, targeted cognitive processes in isolation, and as of yet no system exists that integrates a broad range of capabilities or presents a general solution to autonomous acquisition of a large set of skills. Among the reasons for this are the highly limited machine learning and adaptation techniques available, and the inherent complexity of integrating numerous cognitive and learning capabilities in a coherent architecture. In this paper we review selected systems and architectures built expressly to address integrated skills. We highlight principles and features of these systems that seem promising for creating generally intelligent systems with some level of autonomy, and discuss them in the context of the development of future cognitive architectures. Autonomy is a key property for any system to be considered generally intelligent, in our view; we use this concept as an organizing principle for comparing the reviewed systems. Features that remain largely unaddressed in present research, but seem nevertheless necessary for such efforts to succeed, are also discussed.

Towards a General Attention Mechanism for Embedded Intelligent Systems

“…However, some notable exceptions exist that attempt to address the issues and requirements identified in the previous section. For a more general review of the below architectures, see [15].…”

“…In this respect we discuss how the attention mechanism presented can -2 -DOI: 10.5963/IJCSAI0401001 be used for managing meta-cognitive operation and architectural self-growth; two fundamental functions of AGI systems (cf. [15]). …”

Motivation Management in AGI Systems

“…Many authors have expressed the opinion that a truly intelligent system should be "autonomous" [5,6,17,4] or "self-motivated" [2], though what that exactly means differ from author to author. Intuitively speaking, the consensus is that such a system should behave according to goals of its own choice or creation.…”

“…In the context of AGI, some related topics have been discussed from different perspectives [1][2][3][4], though there are still many issues to be resolved. In this paper, we do not focus on the content of goals in AGI systems, like [1,3], but on the general properties of goals, as well as on how they should be managed in the system.…”

On Attention Mechanisms for AGI Architectures:A Design Proposal

“…Our work so far has not only resulted in the new attention mechanism presented here but also greatly affected the kinds of architectures we consider to be relevant to AGI research -architecture and attention are co-dependent. In that respect we discuss how the attention mechanism presented can be used for managing meta-cognitive operation and architectural self-growth, two fundamental functions of AGI systems (Thórisson & Helgason 2012). …”