Foundations of a Constructivist Memory-Based approach to Cognitive Robotics:
Synthesis of a Theoretical Framework and Application Case Studies
Cognitive robotics are applicable to many aspects of modern society. These artificial agents may also be used as platforms to investigate of the nature and function of cognition itself through the creation and manipulation of biologically-inspired cognitive architectures. However, the flexibility and robustness of current systems are limited by the restricted use of previous experience.
Memory thus has a clear role in cognitive architectures, as a means of linking past experience to present and future behaviour. Current cognitive robotics architectures typically implement a version of Working Memory - a functionally separable system that forms the link between long-term memory (information storage) and cognition (information processing). However, this division of function gives rise to practical and theoretical problems, particularly regarding the nature, origin and use of the information held in memory and used in the service of ongoing behaviour.
The aim of this work is to address these problems by synthesising a new approach to cognitive robotics, based on the perspective that cognition is fundamentally concerned with the manipulation and utilisation of memory. A novel theoretical framework is proposed that unifies memory and control into a single structure: the Memory-Based Cognitive Framework (MBCF). It is shown that this account of cognitive functionality requires the mechanism of constructivist knowledge formation through ongoing environmental interaction, the explicit integration of agent embodiment, and a value system to drive the development of coherent behaviours.
A novel robotic implementation - the Embodied MBCF Agent (EMA) - is introduced to illustrate and explore the central features of the MBCF. By encompassing aspects of both network structures and explicit representation schemes, neural and non-neural inspired processes are integrated to an extent not possible in current approaches.
This research validates the memory-based approach to cognitive robotics, providing the foundation for the application of these principles to higher-level cognitive competencies.