The theory of belief revision and merging has recently been applied to judgement aggregation. In this paper I argue that judgements are best aggregated by merging the evidence on which they are based, rather than by directly merging the judgements themselves. This leads to a threestep strategy for judgement aggregation. First, merge the evidence bases of the various agents using some method of ...

Partially Observable Markov Decision Processes (POMDP) provide a standard framework for sequential decision making in stochastic environments. In this setting, an agent takes actions and receives observations and rewards from the environment. Many POMDP solution methods are based on computing a belief state, which is a probability distribution over possible states in which the agent could be. T...

This paper studies decision making for Wal­ ley's partially consonant belief functions (pcb ) . In a pcb, the set of foci are par­ titioned. Within each partition, foci are nested. The pcb class includes probability and possibility functions as extreme cases. We adopt an axiomatic system, similar in spirit to von Neumann and Morgenstern's ax­ ioms for preferences leading to the linear util­ ity...

Variational inference algorithms such as belief propagation have had tremendous impact on our ability to learn and use graphical models, and give many insights for developing or understanding exact and approximate inference. However, variational approaches have not been widely adoped for decision making in graphical models, often formulated through influence diagrams and including both centrali...

We propose a probabilistic-logical framework for group decision-making. Its main characteristic is that we derive group preferences from agents’ beliefs and utilities rather than from their individual preferences as done in social choice approaches. This can be more appropriate when the individual preferences hide too much of the individuals’ opinions that determined their preferences. We intro...

Multiple attribute decision analysis (MADA) problems in the situation of belief group decision making (BGDM) are a special class of decision problems, where the attribute evaluations of each decision maker (DM) are represented by belief functions. In order to solve these special problems, in this paper, TOPSIS (technique for order preference by similarity to ideal solution) model is extended by...

The sure thing principle and the law of total probability are basic laws in classic probability theory. A disjunction fallacy leads to the violation of these two classical probability laws. In this paper, a new quantum dynamic belief decision making model based on quantum dynamic modelling and DempsterShafer (D-S) evidence theory is proposed to address this issue and model the real human decisi...

Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at http://www.jstor.org/page/info/about/policies/terms.jsp. JSTOR's Terms and Conditions of Use provides, in part, that unless you have obtained prior permission, you may not download an entire issue of a journal or multiple copies of articles, and you may use content in the JSTOR archive o...

Rational agents should update their beliefs in the light of new evidence. Equally, changes in belief should depend only on the quality of the evidence, and not on factors such as the order in which the evidence is acquired, or whether intermediate judgements are requested during evidence acquisition. In contrast we show that requests for intermediate judgments can inhibit belief updating for re...