Game Theory Models of Intelligent Actors in Reliability Analysis: An Overview of the State of the Art

Author(s):  
Seth D. Guikema
2013 ◽  
Vol 15 (03) ◽  
pp. 1340015 ◽  
Author(s):  
VITO FRAGNELLI ◽  
STEFANO GAGLIARDO

Location problems describe those situations in which one or more facilities have to be placed in a region trying to optimize a suitable objective function. Game theory has been used as a tool to solve location problems and this paper is devoted to describe the state-of-the-art of the research on location problems through the tools of game theory. Particular attention is given to the problems that are still open in the field of cooperative location game theory.


Author(s):  
Wulf Albers ◽  
Werner Güth ◽  
Peter Hammerstein ◽  
Benny Moldovanu ◽  
Eric van Damme

Author(s):  
Lars Kotthoff ◽  
Alexandre Fréchette ◽  
Tomasz Michalak ◽  
Talal Rahwan ◽  
Holger H. Hoos ◽  
...  

Assessing the progress made in AI and contributions to the state of the art is of major concern to the community. Recently, Frechette et al. [2016] advocated performing such analysis via the Shapley value, a concept from coalitional game theory. In this paper, we argue that while this general idea is sound, it unfairly penalizes older algorithms that advanced the state of the art when introduced, but were then outperformed by modern counterparts. Driven by this observation, we introduce the temporal Shapley value, a measure that addresses this problem while maintaining the desirable properties of the (classical) Shapley value. We use the tempo- ral Shapley value to analyze the progress made in (i) the different versions of the Quicksort algorithm; (ii) the annual SAT competitions 2007–2014; (iii) an annual competition of Constraint Programming, namely the MiniZinc challenge 2014–2016. Our analysis reveals novel insights into the development made in these important areas of research over time.


2005 ◽  
Vol 20 (1) ◽  
pp. 63-90 ◽  
Author(s):  
KARL TUYLS ◽  
ANN NOWÉ

In this paper we survey the basics of reinforcement learning and (evolutionary) game theory, applied to the field of multi-agent systems. This paper contains three parts. We start with an overview on the fundamentals of reinforcement learning. Next we summarize the most important aspects of evolutionary game theory. Finally, we discuss the state-of-the-art of multi-agent reinforcement learning and the mathematical connection with evolutionary game theory.


Author(s):  
T. A. Welton

Various authors have emphasized the spatial information resident in an electron micrograph taken with adequately coherent radiation. In view of the completion of at least one such instrument, this opportunity is taken to summarize the state of the art of processing such micrographs. We use the usual symbols for the aberration coefficients, and supplement these with £ and 6 for the transverse coherence length and the fractional energy spread respectively. He also assume a weak, biologically interesting sample, with principal interest lying in the molecular skeleton remaining after obvious hydrogen loss and other radiation damage has occurred.


2003 ◽  
Vol 48 (6) ◽  
pp. 826-829 ◽  
Author(s):  
Eric Amsel
Keyword(s):  

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