Issues on the Logical Foundations of Knowledge Representation for Intelligent Autonomous Agents
Shengming Zhou, Yuanxiu Liao, Suqin Tang · 2012
This paper discusses the issues on the logical foundations of knowledge representation for intelligent autonomous agents. We analyze the limitations of the mathematical logic approaches in knowledge representations and show that classical semantic interpretations are not suitable for expressing the autonomous knowledge of agents. We propose a novel logical framework in which the semantic interpretations are not based on the models, but on the sensors of agents. We also illustrate how agents can interpret formulas in autonomously.