Interactive dynamic influence diagrams (I-DIDs) offer a transparent and semantically clear representation for the sequential decision-making problem over multiple time steps in the presence of other interacting agents. Solving I-DIDs exactly involves knowing the solutions of possible models of the other agents, which increase exponentially with the number of time steps. We present a method of s...

Abstr act: Many real world models can be characterized as weak, m�aning that there is significant uncertainty in both the data input and inferences. This lack of determinism makes it especially difficult for users of computer decision aids to understand and have confidence in the models. This paper presents a representation for uncertainty and utilities that serves as a framework for graphical ...

Modeling the perceived behaviors of other agents improves the performance of an agent in multiagent interactions. We utilize the language of interactive influence diagrams to model repeated interactions between the agents, and ascribe procedural models to other agents. Procedural models offer the benefit of understanding how others arrive at their behaviors. As model spaces are often bounded, t...

In this paper we will survey the history of Influence Diagrams from their origin in Decision Theory to modern AI uses. We will compare the various methods that have been used to find an optimal strategy for a given influence diagram. These methods have various advantages under different assumptions and there is a progression to the present of richer, more general solutions. We also look at an a...

A key challenge in information retrieval is the use of contextual evidence within the ad-hoc retrieval. Our contribution is particularly based on the belief that contextual retrieval is a decision making problem. For this reason we propose to apply influence diagrams which are extension of Bayesian networks to such problems, in order to solve the hard problem of user based relevance estimation....

We consider an active information system, which aims to notify a traveler timely about a likely delay. Besides providing the right content, it should also wait for the best time for notification. This is especially true for mobile information services, where every notification may irritate the recipient. We formulate and solve such a problem involving best choices both for content and time of n...

In this paper we present a new class of complexity measures, induced by a new data structure for representing k-valued functions (operations), called minor decision diagram. The results are presented in terms of MultiValued Logic circuits (MVL-circuits), ordered decision diagrams, formulas and minor decomposition trees. When assigning values to some variables in a function f the resulting funct...

This paper is about reducing influence dia­ gram (ID) evaluation into Bayesian network (BN) inference problems. Such reduction is interesting because it enables one to read­ ily use one's favorite BN inference algorithm to efficiently evaluate IDs. Two such reduc­ tion methods have been proposed previously (Cooper 1988, Shachter and Peot 1992). This paper proposes a new method. The BN in­ feren...

This study examines some of the important organizational consequences of the fashion phenomenon in information technology. An IT fashion is an information technology transitorily collectively believed as new, efficient, and at the forefront of practice. Using data collected from published discourse and annual corporate IT budgets, I have found that companies associated with IT fashions did not ...

We discuss the phenomenon of system tailoring in the context of data from an observational study of anaesthesia. We found that anaesthetists tailor their monitoring equipment so that the auditory alarms are more informative. However, the occurrence of tailoring by anaesthetists in the operating theatre was infrequent, even though the flexibility to tailor exists on many of the patient monitorin...