LAUSR

Traditionally, studies on technical communication (TC) are based on stochastic modeling and manipulation. This is not sufficient for semantic communication (SC) where semantic elements are logically connected, rather than stochastically correlated. To fill this void, by leveraging a logical programming language called probabilistic logic (ProbLog), we propose a unified approach to semantic information and communication through the interplay between TC and SC. Building on the well-established existing TC layer, we introduce, in this paper, a SC layer that utilizes knowledge bases of communicating parties for the exchange of semantic information. These knowledge bases are logically described, manipulated, and exploited using ProbLog. To allow efficient interactions between SC and TC layers, various measures are proposed in this paper using the entropy of a clause in a knowledge base. These measurements can account for various technical problems in SC, such as message selection to improve the receiver’s knowledge base. Extending this, we present few selected examples of how the SC and TC layers interact with each other, s while taking into account constraints of physical channels and efficiently utilizing channel resources.