Autonomous driving paper index
Knowledge and Information in Epistemic Dynamics
One-line summary
The paper proposes a general theory of cognitive systems, inverting the conventional rela- tionship between information and knowledge.
Engineering notes
Key topics: autonomous driving. See the paper for implementation details and experimental results.
Chinese explanation / 中文解读
中文解读待补充：本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。
Original abstract
The paper proposes a general theory of cognitive systems, inverting the conventional rela- tionship between information and knowledge. While classical approaches define knowledge as the result of processing information, we posit that knowledge is a primitive concept, and information is a consequence of the knowledge assimilation process. A general definition of a cognitive system is given, and a corresponding measure of epistemic information is defined such that Shannon’s information quantity corresponds to a particular simple case of epistemic information. This perspective enables us to demonstrate the necessity of internal states of a cognitive system that are not accessible to the knowledge, by connecting cognitive systems to formal theories and showing a strong relationship with classical incompleteness results of math- ematical logic. The notion of epistemic levels highlights a rigorous setting for clear distinctions among concepts such as learning, meaning, understanding, consciousness, and intelligence. The role of AI in developing deeper and more accurate models of cognition is argued, which in turn could suggest new relevant theories and architectures in the development of artificial intelligence agents.
Links and sources
Need this topic turned into a technical roadmap?
Full Self Driving can prepare a custom autonomous driving literature review, code map, dataset map, and B2B technology assessment.
Request B2B research
Comments