Long-term autonomy of robotic systems implicitly requires dependable
platforms that are able to naturally handle hardware and software faults,
problems in behaviors, or lack of knowledge. Model-based dependable platforms
additionally require the application of rigorous methodologies during the
system development, including the use of correct-by-construction techniques to
implement robot behaviors. As the level of autonomy in robots increases, so do
the cost of offering guarantees about the dependability of the system.
Certifiable dependability of autonomous robots, we argue, can benefit from
formal models of the integration of several cognitive functions, knowledge
processing, reasoning, and meta-reasoning. Here we put forward the case for a
generative model of cognitive architectures for autonomous robotic agents that
subscribes to the principles of model-based engineering and certifiable
dependability, autonomic computing, and knowledge-enabled robotics.

文章提出了利用认知结构生成模型的方式，以模型为基础的工程和可证明的可靠性、自主计算和知识启用机器人学来获得认证可靠性的自治机器人的可证明可靠性可以受益于几种认知功能，知识处理，推理和元论证的集成的形式化模型。