scholarly journals Belief, information acquisition, and trust in multi-agent systems—A modal logic formulation

2003 ◽  
Vol 149 (1) ◽  
pp. 31-60 ◽  
Author(s):  
Churn-Jung Liau
2013 ◽  
Vol 651 ◽  
pp. 943-948
Author(s):  
Zhi Ling Hong ◽  
Mei Hong Wu

In multi-agent systems, a number of autonomous pieces of software (the agents) interact in order to execute complex tasks. This paper proposes a logic framework portrays agent’s communication protocols in the multi-agent systems and a dynamic negotiation model based on epistemic default logic was introduced in this framework. In this paper, we use the constrained default rules to investigate the extension of dynamic epistemic logic, and constrained epistemic extension construct an efficient negotiation strategy via constrained epistemic default reasoning, which guarantees the important natures of extension existence and semi-monotonicity. We also specify characteristic of the dynamic updating when agent learn new knowledge in the logical framework. The method for the information sharing signify the usefulness of logical tools carried out in the dynamic process of information acquisition, and the distributed intelligent information processing show the effectiveness of reasoning default logic in the dynamic epistemic logic theory.


Author(s):  
ALESSIO LOMUSCIO ◽  
MARK RYAN

Intelligent agents must update their knowledge base as they acquire new information about their environment. The modal logic S5n has been designed for representing knowledge bases in societies of agents. Halpern and Vardi have proposed the notion of refinement of S5n Kripke models in order to solve multi-agent problems in which knowledge evolves. We argue that there are some problems with their proposal and attempt to solve them by moving from Kripke models to their corresponding trees. We define refinement of a tree with a formula, show some properties of the notion, and illustrate with the muddy children puzzle. We show how some diagnosis problems in engineering can be modelled as knowledge-based multi-agent systems, and hence how our approach can address them.


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