scholarly journals Quantifying Algorithmic Improvements over Time

2018 ◽  
Author(s):  
Lars Kotthoff ◽  
Alexandre Fréchette ◽  
Tomasz Michalak ◽  
Talal Rahwan ◽  
Holger H. Hoos ◽  
...  
Keyword(s):  
Game Theory ◽  
Shapley Value ◽  
Constraint Programming ◽  
State Of The Art ◽  
The State ◽  
General Idea ◽  
Coalitional Game ◽  
The Shapley Value ◽  
Over Time ◽  
Made In

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.

scholarly journals Vitality Indices are Equivalent to Induced Game-Theoretic Centralities

2021 ◽  
Author(s):  
Oskar Skibski
Keyword(s):  
Game Theory ◽  
Theoretical Analysis ◽  
Shapley Value ◽  
Centrality Measures ◽  
Coalitional Game ◽  
The Shapley Value ◽  
Balanced Contributions ◽  
Game Theoretic ◽  
The Impact ◽  
Coalitional Game Theory

Vitality indices form a class of centrality measures that assess the importance of a node based on the impact its removal has on the network. To date, theoretical analysis of this class is lacking. In this paper, we show that vitality indices can be characterized using the axiom of Balanced Contributions proposed by Myerson in the coalitional game theory literature. We explore the link between both fields and show an equivalence between vitality indices and induced game theoretic centralities based on the Shapley value. Our characterization allows us to easily determine which known centrality measures are vitality indices.

Query Games in Databases

2021 ◽  
Vol 50 (1) ◽  
pp. 78-85
Author(s):  
Ester Livshits ◽  
Leopoldo Bertossi ◽  
Benny Kimelfeld ◽  
Moshe Sebag
Keyword(s):  
Game Theory ◽  
Cooperative Game ◽  
Shapley Value ◽  
Cooperative Game Theory ◽  
The Shapley Value ◽  
Computational Aspects ◽  
Aggregate Query ◽  
Boolean Query

Database tuples can be seen as players in the game of jointly realizing the answer to a query. Some tuples may contribute more than others to the outcome, which can be a binary value in the case of a Boolean query, a number for a numerical aggregate query, and so on. To quantify the contributions of tuples, we use the Shapley value that was introduced in cooperative game theory and has found applications in a plethora of domains. Specifically, the Shapley value of an individual tuple quantifies its contribution to the query. We investigate the applicability of the Shapley value in this setting, as well as the computational aspects of its calculation in terms of complexity, algorithms, and approximation.

Shapley Ranking of Wines

2012 ◽  
Vol 7 (2) ◽  
pp. 169-180 ◽  
Author(s):  
Victor Ginsburgh ◽  
Israël Zang
Keyword(s):  
Game Theory ◽  
Unique Solution ◽  
Cooperative Game ◽  
Shapley Value ◽  
Rank Order ◽  
Jel Classification ◽  
Ranking Method ◽  
The Shapley Value ◽  
Shapley Values

AbstractWe suggest a new game-theory-based ranking method for wines, in which the Shapley Value of each wine is computed, and wines are ranked according to their Shapley Values. Judges should find it simpler to use, since they are not required to rank order or grade all the wines, but merely to choose the group of those that they find meritorious. Our ranking method is based on the set of reasonable axioms that determine the Shapley Value as the unique solution of an underlying cooperative game. Unlike in the general case, where computing the Shapley Value could be complex, here the Shapley Value and hence the final ranking, are straightforward to compute. (JEL Classification: C71, D71, D78)

OPEN PROBLEMS IN COOPERATIVE LOCATION GAMES

2013 ◽  
Vol 15 (03) ◽  
pp. 1340015 ◽  
Author(s):  
VITO FRAGNELLI ◽  
STEFANO GAGLIARDO
Keyword(s):  
Game Theory ◽  
Objective Function ◽  
State Of The Art ◽  
The State ◽  
Location Problems ◽  
Open Problems ◽  
Location Games

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.

A Comprehensive Taxonomy of Dynamic Texture Representation

2023 ◽  
Vol 55 (1) ◽  
pp. 1-39
Author(s):  
Thanh Tuan Nguyen ◽  
Thanh Phuong Nguyen
Keyword(s):  
Large Scale ◽  
Environmental Changes ◽  
State Of The Art ◽  
The State ◽  
Future Research ◽  
Research Activities ◽  
Potential Applications ◽  
Benchmark Datasets ◽  
Negative Impacts ◽  
Made In

Representing dynamic textures (DTs) plays an important role in many real implementations in the computer vision community. Due to the turbulent and non-directional motions of DTs along with the negative impacts of different factors (e.g., environmental changes, noise, illumination, etc.), efficiently analyzing DTs has raised considerable challenges for the state-of-the-art approaches. For 20 years, many different techniques have been introduced to handle the above well-known issues for enhancing the performance. Those methods have shown valuable contributions, but the problems have been incompletely dealt with, particularly recognizing DTs on large-scale datasets. In this article, we present a comprehensive taxonomy of DT representation in order to purposefully give a thorough overview of the existing methods along with overall evaluations of their obtained performances. Accordingly, we arrange the methods into six canonical categories. Each of them is then taken in a brief presentation of its principal methodology stream and various related variants. The effectiveness levels of the state-of-the-art methods are then investigated and thoroughly discussed with respect to quantitative and qualitative evaluations in classifying DTs on benchmark datasets. Finally, we point out several potential applications and the remaining challenges that should be addressed in further directions. In comparison with two existing shallow DT surveys (i.e., the first one is out of date as it was made in 2005, while the newer one (published in 2016) is an inadequate overview), we believe that our proposed comprehensive taxonomy not only provides a better view of DT representation for the target readers but also stimulates future research activities.

A Study of the State of the Art in Synthetic Emotional Intelligence in Affective Computing

2020 ◽  
pp. 1199-1212
Author(s):  
Syeda Erfana Zohora ◽  
A. M. Khan ◽  
Arvind K. Srivastava ◽  
Nhu Gia Nguyen ◽  
Nilanjan Dey
Keyword(s):  
Emotional Intelligence ◽  
Affective Computing ◽  
Ethical Issues ◽  
State Of The Art ◽  
Real Life ◽  
Life Time ◽  
The State ◽  
Point Of View ◽  
General Idea ◽  
Tremendous Amount

In the last few decades there has been a tremendous amount of research on synthetic emotional intelligence related to affective computing that has significantly advanced from the technological point of view that refers to academic studies, systematic learning and developing knowledge and affective technology to a extensive area of real life time systems coupled with their applications. The objective of this paper is to present a general idea on the area of emotional intelligence in affective computing. The overview of the state of the art in emotional intelligence comprises of basic definitions and terminology, a study of current technological scenario. The paper also proposes research activities with a detailed study of ethical issues, challenges with importance on affective computing. Lastly, we present a broad area of applications such as interactive learning emotional systems, modeling emotional agents with an intention of employing these agents in human computer interactions as well as in education.

The Technique of Raman Spectroscopy: A State-of-the-Art Comparison to Infrared

1971 ◽  
Vol 25 (4) ◽  
pp. 430-439 ◽  
Author(s):  
Howard J. Sloane
Keyword(s):  
Raman Spectroscopy ◽  
State Of The Art ◽  
The State ◽  
Point Of View ◽  
Complementary Information ◽  
Future Outlook ◽  
Sample Handling ◽  
Advantages And Disadvantages ◽  
Sampling Procedures ◽  
Made In

This paper in a tabulated summary format discusses the state-of-the-art of Raman spectroscopy for commercially available instrumentation. A comparison to infrared is made in terms of (I) instrumentation, (II) sample handling, and (III) applications. Although the two techniques yield similar and often complementary information, they are quite different from the point of view of instrumentation and sampling procedures. This leads to various advantages and disadvantages or limitations for each. These are discussed as well as the future outlook.

A Shapley Value Analysis of the Proposed Canadian Constitutional Amendment Scheme

1973 ◽  
Vol 6 (1) ◽  
pp. 140-143 ◽  
Author(s):  
D.R. Miller
Keyword(s):  
Game Theory ◽  
Shapley Value ◽  
Constitutional Amendment ◽  
Value Analysis ◽  
A Value ◽  
The Shapley Value ◽  
Relative Value ◽  
Individual Player

The interactions of a group of non-identical voting units may be studied by applying the concept of the Shapley value from n-person co-operative game theory. In this theory one assumes that voting units, or players, may form coalitions of various kinds in order to achieve success in the game, and one may assign a “value” to each such coalition based on what it can accomplish against arbitrary coalitions of the remaining players. The relative value of an individual player is calculated by considering how much he brings to each coalition he might join, that is, by how much the value of that coalition increases because of his membership, and summing this figure over all coalitions of which he could be a part.

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