Generic Cognitive Architecture for Real-Time, Embedded Cognitive Systems

Abstract: The problem of integrated cognition , analyzed in the thesis, belongs to a multi-disciplinary area of cognitive engineering. The multi-disciplinary focusing on cognitive models and real-time embedded systems, such as mobile robots, helps to reveal a broader and deeper understanding of robotics as part of everyday life and society. Over the past decades many cognitive architectures have been proposed and steadily developed, based on different approaches and methodologies, but still current cognitive architectures are far from the goal of covering the requirements for general intelligence. Recent research in the area of evolutionary algorithms and genetic programming is used in this study as an inspiration for developing the new version of integrated cognitive architecture, and the knowledge of human brain structure and functions is applied to the architecture as well. In this study a survey of cognitive architectures is performed, a version of biologically inspired hybrid cognitive architecture is developed. This architecture is influenced by a contemporary research in evolutionary algorithms and genetic programming. Some modules of the architecture are applied to a mobile robot in a simulated environment.