This paper motivates the study of decision theory as necessary for aligning smarter-thanhuman artificial systems with human interests. We discuss the shortcomings of two standard formulations of decision theory, and demonstrate that they cannot be used to describe an idealized decision procedure suitable for approximation by artificial systems. We then explore the notions of policy selection an...

I explore the prospects for modelling epistemic rationality (in the probabilist setting) via an epistemic decision theory, in consequentialist spirit. Previous work has focussed on cases in which the truth-values of the propositions in which the agent is selecting credences do not depend, either causally or merely evidentially, on the agent’s choice of credences. Relaxing that restriction leads...

I explore the prospects for modelling epistemic rationality (in the probabilist setting) via an epistemic decision theory, in a consequentialist spirit. Previous work has focused on cases in which the truth-values of the propositions in which the agent is selecting credences do not depend, either causally or merely evidentially, on the agent’s choice of credences. Relaxing that restriction lead...

We present a “quantum decision theory” (QDT) of decision making based on the mathematical theory of separable Hilbert spaces on the continuous field of complex numbers. This mathematical structure captures the effect of superposition of composite prospects, including many incorporated intentions, which allows us to describe a variety of interesting fallacies and anomalies that have been reporte...

This paper sets out to solve the Sleeping Beauty problem and various related anthropic (self-locating belief) problems, not through the calculation of anthropic probabilities, but through finding the correct decision to make. Given certain simple assumptions, it turns out to be possible to do so without knowing the underlying anthropic probabilities. Most common anthropic problems are underspec...

this paper assumes the cell formation problem as a distributed decision network. it proposes an approach based on application and extension of information theory concepts, in order to analyze informational complexity in an agent- based system, due to interdependence between agents. based on this approach, new quantitative concepts and definitions are proposed in order to measure the amount of t...

in this paper, a novel hybrid model based on neural network and game theory is proposed to support the analyzers in oil market. in this model, first the neural network is utilized to learn the oil prices associated with opec production level and usa imports level. then the learned neural network is applied by a game model. finally the nash equilibrium points of the game present the optimum deci...

“rational choice model” is one of the economics theories which developed into sociology, politics, and anthropology and was applied to understand and justify some phenomena.  according to this hypothesis, the basis of decision making is improvements, enjoyment and suffering disposal. people always do all necessary calculations in each and every decision making and then adopt a rational decision...

In this paper, target differentiation based on pattern of data which are obtained by a set of two ultrasonic sensors is considered. A neural network based target classifier is applied to these data to categorize the data of each sensor. Then the results are fused together by Dempster–Shafer theory (DST) and Dezert–Smarandache theory (DSmT) to make final decision. The Generalized Aggregated Unce...