Adjusting a Knowledge-Based Algorithm for Multi-agent Communication for CPS

Author(s):  
Egon van Baars ◽  
Rineke Verbrugge
Author(s):  
Zojan Memon ◽  
◽  
Akhtar Hussain Jalbani ◽  
Mohsin Shaikh ◽  
Rafia Naz Memon ◽  
...  

Author(s):  
Yì N Wáng ◽  
Xu Li

Abstract We introduce a logic of knowledge in a framework in which knowledge is treated as a kind of belief. The framework is based on a standard KD45 characterization of belief, and the characterization of knowledge undergoes the classical tripartite analysis that knowledge is justified true belief, which has a natural link to the studies of logics of evidence and justification. The interpretation of knowledge avoids the unwanted properties of logical omniscience, independent of the choice of the base logic of belief. We axiomatize the logic, prove its soundness and completeness and study the computational complexity results of the model checking and satisfiability problems. We extend the logic to a multi-agent setting and introduce a variant in which belief is characterized in a weaker system to avoid the problem of logical omniscience.


Author(s):  
R. Keith Sawyer

Sociology should be the foundational science of social emergence. But to date, sociologists have neglected emergence, and studies of emergence are more common within microeconomics. Moving forward, I argue that a science of social emergence requires two advances beyond current approaches—and that sociology is better positioned than economics to make these advances. First, consistent with existing critiques of microeconomics, I argue that we need a more sophisticated representation of individual agents. Second, I argue that multi-agent models need a more sophisticated representation of interaction processes. The agent communication languages currently used by multi-agent systems researchers are not appropriate for modeling human societies. I conclude by arguing that the scientific study of interaction and emergence will have to migrate out of microeconomics and become a part of sociology. Sociologists, for their part, should embrace multi-agent modeling to pursue a more rigorous study of these traditional sociological issues.


Author(s):  
Rahul Singh

Organizations use knowledge-driven systems to deliver problem-specific knowledge over Internet-based distributed platforms to decision-makers. Increasingly, artificial intelligence (AI) techniques for knowledge representation are being used to deliver knowledge-driven decision support in multiple forms. In this chapter, we present an Architecture for knowledge-based decision support, delivered through a Multi-Agent Architecture. We illustrate how to represent and exchange domain-specific knowledge in XML-format through intelligent agents to create exchange and use knowledge to provide intelligent decision support. We show the integration of knowledge discovery techniques to create knowledge from organizational data; and knowledge repositories (KR) to store, manage and use data by intelligent software agents for effective knowledge-driven decision support. Implementation details of the architecture, its business implications and directions for further research are discussed.


Sign in / Sign up

Export Citation Format

Share Document