SOAR: An architecture for general intelligence

One approach in pursuit of general intelligent agents has been to concentrate on the underlying cognitive architecture, of which Soar is a prime example. In the past, Soar has relied on a minimal number of architectural modules together with purely symbolic representations of knowledge. This paper presents the cognitive architecture approach to general intelligence and the traditional, symbolic Soar architecture. This is followed by major additions to Soar: nonsymbolic representations, new learning mechanisms, and long-term memories.

2012

2017

The term " Cognitive Architectures " indicates both abstract models of cognition, in natural and artificial agents, and the software instantiations of such models which are then employed in the field of Artificial Intelligence (AI). The main role of Cognitive Architectures in AI is that one of enabling the realization of artificial systems able to exhibit intelligent behavior in a general setting through a detailed analogy with the constitutive and developmental functioning and mechanisms underlying human cognition. We provide a brief overview of the status quo and of the potential role that Cognitive Architectures may serve in the fields of Computational Cognitive Science and Artificial Intelligence (AI) research.

… of the 2008 conference on Artificial …, 2008

Cognitive architectures play a vital role in providing blueprints for building future intelligent systems supporting a broad range of capabilities similar to those of humans. How useful are existing architectures for creating artificial general intelligence? A critical survey of the state of the art in cognitive architectures is presented providing a useful insight into the possible frameworks for general intelligence. Grand challenges and an outline of the most promising future directions are described. : "W. Duch".

1991

In this article we take a step towards providing an analysis of the Soar architecture as a basis for general intelligence. Included are discussions of the basic assumptions underlying the development of Soar, a description of Soar cast in terms of the theoretical idea of multiple levels of description, an example of Soar performing multi-column subtraction, and three analyses of Soar: its natural tasks, the sources of its power, and its scope and limits

2004

This paper describes a cognitively-oriented architecture that facilitates the development of expertise. Based on knowledge about human decision making, it integrates multiple representations, multiple decision-making rationales, and multiple learning methods to support the construction of intelligent systems. A constraint solver implemented within the architecture engineers a problem-solving paradigm. This program manages a variety of search heuristics and learns new ones. It can transfer what it learns on simple problems to solve more difficult ones, and can readily export its knowledge to ordinary solvers. It is intended both as a learner and as a test bed for the constraint community. Both the program and the architecture are ambitious, ongoing research projects to support human reasoning.

this paper presents a review of "How AI, cognitive science and DM are combined to develop intelligent agents", and how the paradigm first shifted from AI to Data mining and then towards combination of data mining and artificial intelligence. The paper will also provide a state-of-the-art account of the cognitive architectures. It also gives a detailed comparative study of all the architectures discussed in the paper. All the survey of data mining and cognitive architecture is done w.r.t Multi agent systems. Therefore, paper will also provide a bird eye view of MAS/ ABMS.

Proceeding of the 2007 conference on Advances in …, 2007

Since the early nineties, interest has been growing in different facets of cognitive architectures and, inspired by advances in AI tools and methodologies, competing proposals have been put forward by various research communities. This gives the task of evaluating the various architectures importance. This paper outlines our proposals for the design and running of a Cognitive Architectures Competition to tackle this issue. Especially, this will involve creating an international community of researchers, developers and users, current and potential, who will have vested interests in the design of the competition. To evaluate entries, the competition's community will be required to develop a classification of Cognitive Architecture-based systems' current, and near future, capabilities and their potential range of desirable, practical applications. The community will need to address important technical issues and in doing so will help set a future research and development agenda.

In this paper, we examine the motivations for research on cognitive architectures and review some candidates that have been explored in the literature. After this, we consider the capabilities that a cognitive architecture should support, some properties that it should exhibit related to representation, organization, performance, and learning, and some criteria for evaluating such architectures at the systems level. In closing, we discuss some open issues that should drive future research in this important area.