Agent-Based Simulations with Beliefs and SPARQL-Based Ask-Reply Communication

摘要

This paper presents the results of extending an agent-based simulation framework by adding a full-fledged model of beliefs and by supporting ask-reply communication with the help of the W3C RDF query language SPARQL. Beliefs are the core component of any cognitive agent architecture. They are also the basis of ask-reply communication between agents, which allows social learning. Our approach supports the conceptual distinctions between facts and beliefs, and between sincere answers and lies.