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The papers in these Proceedings were presented at the Nineteenth ACM Conference on Economics and Computation (EC'18), held between June 18 and 22, 2018, at Cornell University in Ithaca, New York, USA. Since 1999 the ACM Special Interest Group on Electronic Commerce (SIGecom) has sponsored EC, the leading scientific conference on advances in theory, systems, and applications at the interface of economics and computation, including applications to electronic commerce. Each paper was reviewed by at least three program committee members and two senior program committee members on the basis of significance, scientific novelty, technical quality, readability, and relevance to the conference. Following the tradition of recent iterations of the conference, the authors were asked to align their submission with one or two of the tracks. The next table summarizes the number of submissions and the number of accepted papers for each possible combination of tracks Of the 70 accepted papers, 36 are published in these Proceedings. The remaining 34, at the authors' request, are included as abstracts with pointers to full working papers that the authors guarantee to be reliable for at least two years. This option accommodates the practices of fields outside of computer science in which conference publishing can preclude journal publishing. We expect that many of the papers in these Proceedings will appear at a later date in a more polished and complete form in scientific journals. Papers were presented in two parallel sessions. To emphasize commonalities among the problems studied at EC, and to encourage discussion at the conference, sessions were organized by topic rather than by focus area, and no indication of a paper's focus area(s) was given at the conference or appears in these proceedings.

Algorithms

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Since the launch, in 1965, of the key notion of a fuzzy subset by Lotfi A. Zadeh, this concept has succeeded in growing interest and development. Nowadays, it is undoubtedly one of the most powerful and appealing branches of mathematics. Its range of applications is wide and multidisciplinary, starting from computer sciences and artificial intelligence, but also touching on a vast set of scientific disciplines (physics, engineering, medicine, economics, social choice, etc.). The present Special Issue is devoted to introducing new trends on this theory, from an interdisciplinary point of view, and looking for a wide coverage of topics related to fuzzy set and systems.

Approximation algorithms.

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Since the launch, in 1965, of the key notion of a fuzzy subset by Lotfi A. Zadeh, this concept has succeeded in growing interest and development. Nowadays, it is undoubtedly one of the most powerful and appealing branches of mathematics. Its range of applications is wide and multidisciplinary, starting from computer sciences and artificial intelligence, but also touching on a vast set of scientific disciplines (physics, engineering, medicine, economics, social choice, etc.). The present Special Issue is devoted to introducing new trends on this theory, from an interdisciplinary point of view, and looking for a wide coverage of topics related to fuzzy set and systems.

Approximation algorithms.

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Since the launch, in 1965, of the key notion of a fuzzy subset by Lotfi A. Zadeh, this concept has succeeded in growing interest and development. Nowadays, it is undoubtedly one of the most powerful and appealing branches of mathematics. Its range of applications is wide and multidisciplinary, starting from computer sciences and artificial intelligence, but also touching on a vast set of scientific disciplines (physics, engineering, medicine, economics, social choice, etc.). The present Special Issue is devoted to introducing new trends on this theory, from an interdisciplinary point of view, and looking for a wide coverage of topics related to fuzzy set and systems.

Approximation algorithms.

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This specialized and authoritative book contains an overview of modern approaches to constructing approximations to solutions of ill-posed operator equations, both linear and nonlinear. These approximation schemes form a basis for implementable numerical algorithms for the stable solution of operator equations arising in contemporary mathematical modeling, and in particular when solving inverse problems of mathematical physics. The book presents in detail stable solution methods for ill-posed problems using the methodology of iterative regularization of classical iterative schemes and the techniques of finite dimensional and finite difference approximations of the problems under study. Special attention is paid to ill-posed Cauchy problems for linear operator differential equations and to ill-posed variational inequalities and optimization problems. The readers are expected to have basic knowledge in functional analysis and differential equations. The book will be of interest to applied mathematicians and specialists in mathematical modeling and inverse problems, and also to advanced students in these fields. ContentsIntroductionRegularization Methods For Linear EquationsFinite Difference MethodsIterative Regularization MethodsFinite-Dimensional Iterative ProcessesVariational Inequalities and Optimization Problems

Algorithms. --- Algorithms --- Algorism --- Algebra --- Arithmetic --- Foundations