Theory and applications of difference evaluation functions

ABSTRACT The credit assignment problem (which agents get credit or blame for system performance) is a key research area. For a team of agents collaborating to achieve a goal, the effectiveness of each individual agent must be calculated in order to give adequate feedback to each agent. We use the Difference Evaluation Function to find agent-specific feedback. The Difference Evaluation Function has given excellent empirical results in many domains, including air traffic control and mobile robot control. Though there has been some theoretical work that shows why Difference Evaluation Functions improve system performance, there has been no work to show when and under what conditions such improvements are realized. We apply an evolutionary game-theoretic analysis to show the theoretical advantages of the Difference Evaluation Function. We then focus on how to apply these multiagent learning methods to optimize distributed sensor networks in advanced power generation systems

Sur la décombinaison de fonctions de croyance

International audienceThe evidence combination is a kind of decision-level information fusion in the theory of belief functions. Given two basic belief assignments (BBAs) originated from different sources, one can combine them using some combination rule, e.g., Dempster's rule to expect a better decision result. If one only has a combined BBA, how to determine the original two BBAs to combine? This can be considered as a defusion of information. This is useful, e.g., one can analyze the difference or dissimilarity between two different information sources based on the BBAs obtained using evidence decombination. Therefore, in this paper, we research on such a defusion in the theory of belief functions. We find that it is a well-posed problem if one original BBA and the combined BBA are both available, and it is an under-determined problem if both BBAs to combine are unknown. We propose an optimization-based approach for the evidence decombination according to the criteria of divergence maximization. Numerical examples are provided illustrate and verify our proposed decombination approach, which is expected to be used in applications such the difference analysis between information sources in information fusion systems when the original BBAs are discarded, and performance evaluation of combination rules

Understanding Competing Application Usage By Integrating Information System Success Model And Network Externality Theory

The D&M IS Success Model has been widely applied to evaluate the information system now. Since the connections and communications among individuals tend to be closer, this study introduces network externalities to the existing model In addition, although previous studies view the information quality, system quality and service quality as independent variables without interactions, this research investigates the inter-relationships among them. Since there are so many applications with same functions in the competitive market, in this study we also try to understand competing application usage by integrating IS success model to see how individuals make a decision to select one from two choices, and analyze the theory in the relative evaluation by applying comparison by difference (e.g., “user’s satisfaction towards A” minus “user’s satisfaction towards B”). The result shows that network externalities have great significance on three dimensions of quality, and its effect on service quality actually exerts by the mediating effects of information quality and system quality. The service quality was also proved to be affected positively by information quality and system quality. Thus, the current study not only contributes to the current theory by extending the model, but also provides some practical implications

Macdonald's Evaluation Conjectures, Difference Fourier Transform, and Applications

This paper contains the proof of Macdonald's duality and evaluation conjectures, the definition of the difference Fourier transform, the recurrence theorem generalizing Pieri rules, and the action of GL(2,Z) on the Macdonald polynomials at roots of unity.Comment: AMSTe

Implementation of the Combined--Nonlinear Condensation Transformation

We discuss several applications of the recently proposed combined nonlinear-condensation transformation (CNCT) for the evaluation of slowly convergent, nonalternating series. These include certain statistical distributions which are of importance in linguistics, statistical-mechanics theory, and biophysics (statistical analysis of DNA sequences). We also discuss applications of the transformation in experimental mathematics, and we briefly expand on further applications in theoretical physics. Finally, we discuss a related Mathematica program for the computation of Lerch's transcendent.Comment: 23 pages, 1 table, 1 figure (Comput. Phys. Commun., in press