How can I build a smarter database using similarity logic?
Building Intelligent Databases through Similarity: Interaction of Logical and Qualitative Reasoning
This paper proposes a logic-based method for evaluating similarity between knowledge bases, introducing a "similarity property space" to quantify relatedness between concepts. While not directly about multi-agent systems, the framework could be relevant to LLM-based agents by offering a structured way to compare and share knowledge, potentially enabling more nuanced agent interaction and collaboration based on a logical understanding of similarity. The hierarchical organization of knowledge within the framework through "super-categories" could also enable agents to reason at different levels of abstraction, which is crucial for complex problem-solving. The focus on symbolic representation and reasoning in this work aligns with the symbolic capabilities of LLMs, potentially facilitating their integration into logic-based multi-agent frameworks.