A fuzzy rule-based evidential reasoning (FURBER) approach has been proposed recently, where a fuzzy rule-base designed on the basis of a belief structure (called a belief rule base) forms a basis in the inference mechanism of FURBER. This kind of rule-base with both subjective and analytical elements may be difficult to build in particular as the system increases in complexity. In this paper, a...

Mathematical Theory of Evidence called also Dempster-Shafer Theory (DST) is known as a foundation for reasoning when knowledge is expressed at various levels of detail. Though much research effort has been committed to this theory since its foundation, many questions remain open. One of the most important open questions seems to be the relationship between frequencies and the Mathematical Theor...

Some have argued that belief in God is intuitive, a natural (by-)product of the human mind given its cognitive structure and social context. If this is true, the extent to which one believes in God may be influenced by one's more general tendency to rely on intuition versus reflection. Three studies support this hypothesis, linking intuitive cognitive style to belief in God. Study 1 showed that...

Some have argued that belief in God is intuitive, a natural (by-)product of the human mind given its cognitive structure and social context. If this is true, the extent to which one believes in God may be influenced by one’s more general tendency to rely on intuition versus reflection. Three studies support this hypothesis, linking intuitive cognitive style to belief in God. Study 1 showed that...

Over the past few years, point-based POMDP solvers scaled up to produce approximate solutions to mid-sized domains. However, to solve real world problems, solvers must exploit the structure of the domain. In this paper we focus on the topological structure of the problem, where the state space contains layers of states. We present here the Topological Order Planner (TOP) that utilizes the topol...

This paper presents an eficient algorithm for learning a Bayesian belief network (BBN) structure from a database, as well as providing a comparison between two BBN structure fitness functions. A Bayesian belief network is a directed acyclic graph representing conditional expectations. In this paper, we propose a two-phase algorithm. The first phase uses asymptotically correct structure learning...

In this paper we propose an expanded representation of group belief structures. Three key aspects of belief structures are identified – validity, irrelevance, and uncertainty. Validity arises from the amount of valid beliefs that comprise a group’s belief structure, and the amount of invalid (not corresponding to reality) beliefs in the belief structure. Irrelevance represents the represents th...