The Transferable Belief Model is a powerful interpretation of belief function theory where decision making is based on the pignistic transform. Smets has proposed a generalization of the pignistic transform which appears to be equivalent to the Shapley value in the transferable utility model. It corresponds to the situation where the decision maker bets on several hypotheses by associating a su...

We examined decisions based on verbal probability phrases, such as "small chance," "likely," or "doubtful" (we call these phrases verbal probabilities). Verbal probabilities have communicative functions called directionality and can be categorized into positive (e.g., "likely" or "probable") or negative (e.g., “unlikely,” “doubtful”) phrases in terms of their directionality. Previous studies ha...

What is the relation between (a) “full” or “outright” belief and (b) the various levels of confidence that agents can have in the propositions that concern them? This paper argues for a new answer to this question. Decision theory implies that in making decisions, rational agents must treat certain propositions as though they were completely certain; but on most forms of decision theory, these ...

We propose a new approach to value-directed belief state approximation for POMDPs. The valuedirected model allows one to choose approximation methods for belief state monitoring that have a small impact on decision quality. Using a vector space analysis of the problem, we devise two new search procedures for selecting an approximation scheme that have much better computational properties than e...

SNePS is a mature knowledge representation, reasoning, and acting system that has long contained a belief revision subsystem, called SNeBR. SNeBR is triggered when an explicit contradiction is introduced into the SNePS belief space, either because of a user’s new assertion, or because of a user’s query. SNeBR then makes the user decide what belief to remove from the belief space in order to res...

SNePS is a mature knowledge representation, reasoning, and acting system that has long contained a belief revision subsystem, called SNeBR. SNeBR is triggered when an explicit contradiction is introduced into the SNePS belief space, either because of a user’s new assertion, or because of a user’s query. SNeBR then makes the user decide what belief to remove from the belief space in order to res...

This chapter presents a framework for multi-biometric match score fusion when non-ideal conditions cause conflict in the results of different unimodal biometrics classifiers. The proposed framework uses belief function theory to effectively fuse the match scores and density estimation technique to compute the belief assignments. Fusion is performed using belief models such as Transferable Belie...

Purpose – To: evaluate Prospect Theory and Cumulative Prospect Theory as functional models of decision making and risk within various contexts; compare and analyze risk models and decision-making models; evaluate models of stock risk developed by Robert Engle and related models; establish whether the models are related and have the same foundations; relate risk, decision making and options theo...

We provide some objective foundations for a belief revision process in a situation where (i) the decision-maker's initial probabilistic knowledge is imprecise and characterized by the core of a belief function, (ii) expected new data are themselves consistent with a belief function with known focal sets and (iii) the revision process is based on belief function combination. We study the propert...