In this paper, we present the use of sequential decision-making process simulations for base agents in our multi-agent based economic landscape (MABEL) model. The sequential decision-making process described here is a data-driven Markov-Decision Problem (MDP) integrated with stochastic properties. Utility acquisition attributes in our model are generated for each time step of the simulation. We...

contrary to majority of islamic jurists, those who believe in singularity of reality and a certain rule in disagreement cases, in opinion of some of the scholars, the truth and the rule is plural and all of the jurist(modjtahedin) are just. imam mohammad ghazzali is one of these scholars. in his opinion, the theory of proscription (takteah) is incorrect and contradictory. with the exception of ...

The conjunctive weight function is an equivalent representation of a non dogmatic belief function. Denœux recently proposed new rules of combination for belief functions based on pointwise combination of conjunctive weights. This paper characterizes the rules of combination based on the conjunctive weight function that have the vacuous belief function as neutral element. The main result is that...

In this paper, we study how an agent’s belief is affected by her neighbors in a social network. We first introduce a general framework, where every agent has an initial belief on a statement, and updates her belief according to her and her neighbors’ current beliefs under some belief evolution functions, which, arguably, should satisfy some basic properties. Then, we focus on the majority rule ...

Decision fusion in sensor networks enables sensors to improve classification accuracy while reducing the energy consumption and bandwidth demand for data transmission. In this paper, we focus on the decentralized multi-class classification fusion problem in wireless sensor networks (WSNs) and a new simple but effective decision fusion rule based on belief function theory is proposed. Unlike exi...

A new proposal for incorporating new evidence in an agent's knowledge base is presented in this paper. This proposal is based on a semi-qualitative notion of plausibility and on the abductive explanation for the newly observed fact. Plausibility is determined by speciicity relations between the default rules in the agent's knowledge base and by the agent's contingential knowledge. We demonstrat...

Belief Logic Programming (BLP) is a novel form of quantitative logic programming in the presence of uncertain and inconsistent information, which was designed to be able to combine and correlate evidence obtained from non-independent information sources. BLP has non-monotonic semantics based on the concepts of belief combination functions and DempsterShafer theory of evidence. Most importantly,...

Abstract In the field of high-end manufacturing, it is valuable to study few-shot health condition estimation. Although transfer learning and other methods have effectively improved ability learning, they still cannot solve lack prior knowledge. this paper, by combining data enhancement, knowledge reasoning, a generative knowledge-based model proposed achieve First, with effectiveness enhanceme...

This paper extends a programming language for implementing cognitive agents with the capability to explicitly represent beliefs and reason about them. In this programming language, the beliefs of agents are implemented by modal logic programs, where beliefs are represented by explicit modal operators. A distinction is made between a belief base language that can be used to represent an agent’s ...

Abstract: Correct data association between the measurements for the objects and the known tracks is an important content for vehicle tracking study, and is also the base for enhancing the precision of the state estimation for targets in road situation. Based on the evidence theory and fuzzy mathematics, a new data association method between the tracks and the measurements is proposed in the pap...