Cognitive architecture

What is cognitive architecture?

As humans, we have many different cognitive abilities. There is memory, language, perception, problem solving, mental will, attention and other such abilities. The goal in cognitive psychology is to explore the characteristics of such abilities and, if possible, to describe them in formal models.

Accordingly, cognitive architecture is understood to mean the representation of the different skills of cognitive psychology in a computer model. Also the Artificial intelligence (AI) strives towards the goal of fully realising cognitive abilities in machines. In contrast to cognitive architecture, artificial agents use strategies that are not used by humans.

What are criteria of cognitive architecture?

Cognitive architectures have certain criteria. These include the appropriate Structures of data representation, the support of classifications and the support of the Frege principle. In addition, the Criteria of productivity, performance, syntactic generalisation, robustness, adaptability, memory consumption, scalability, independent knowledge gain, such as logical reasoning and correlation detection. to this.

Triangulation, namely the merging of certain data from different sources, is also one of the criteria of cognitive architecture. Another important criterion is compactness with a basic structure that is as simple as possible. A high-performance system that fulfils all these characteristics is IBM's DeepQA.

Cognitive systems are already indispensable in many areas today and they will influence industrial and economic sectors to an ever greater extent in the future. Cognitive systems are the basis for future technologies, such as autonomous driving and other autonomous systems, Industry 4.0 and also the Internet of Things.

Cognitive systems are technical systems that are able to independently develop solutions and suitable strategies for human tasks. These systems are equipped with cognitive abilities and understand contextual content as well as interacting, adapting and learning. In cognitive architecture, it is important that flexible and adaptable software architectures work together in an overall system.

What theories can be found in cognitive science?

The SOAR (state, operator and result) architecture is a problem space search in which operators are applied to states to obtain results. This problem space search is done in the central working memory. Temporary knowledge is managed there. In order to be able to use knowledge, it is retrieved from the long-term memory into the working memory. Knowledge in the long-term memory is completely stored associatively through productions. Matching knowledge units are written into the working memory (with execute) and permanent experience-based learning (chunking) is applied in the process.

Marketable cognitive architectures, as well as artificial intelligence methods and algorithms, are also being used in flight mechanics and flight guidance. machine learning used. Systematic further developments are successfully used in highly automated flight systems.

In addition to SOAR, there are other cognitive architectures. For example, a step-by-step simulation of human behaviour during ACT-R was carried out. The empirical data for this comes from the experiments of cognitive psychology.

Clarion cognitive architecture stores both action-oriented and non-action-oriented knowledge with an implicit form using multilayer neural networks and in an explicit form using symbolic production rules. There are also the architectures LEABRA, LIDA, ART and ICARUS. Each architecture has its particular strengths, but also technical limitations.

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