This book constitutes the thoroughly refereed conference proceedings of the Third International Conference on Algorithmic Decision Theory, ADT 2013, held in November 2013 in Bruxelles, Belgium. The 33 revised full papers presented were carefully selected from more than 70 submissions, covering preferences in reasoning and decision making, uncertainty and robustness in decision making, multi-criteria decision analysis and optimization, collective decision making, learning and knowledge extraction for decision support.

1. 1 Motivations Deciding is a very complex and difficult task. Some people even argue that our ability to make decisions in complex situations is the main feature that distinguishes us from animals (it is also common to say that laughing is the main difference). Nevertheless, when the task is too complex or the interests at stake are too important, it quite often happens that we do not know or we are not sure what to decide and, in many instances, we resort to a decision support technique: an informal one-we toss a coin, we ask an oracle, we visit an astrologer, we consult an expert, we think-or a formal one. Although informal decision support techniques can be of interest, in this book, we will focus on formal ones. Among the latter, we find some well-known decision support techniques: cost-benefit analysis, multiple criteria decision analysis, decision trees, . . . But there are many other ones, sometimes not presented as decision support techniques, that help making decisions. Let us cite but a few examples. * When the director of a school must decide whether a given student will pass or fail, he usually asks each teacher to assess the merits of the student by means of a grade. The director then sums the grades and compares the result to a threshold. * When a bank must decide whether a given client will obtain a credit or not, a technique, called credit scoring, is often used.

This book constitutes the refereed proceedings of the Second International Conference on Algorithmic Decision Theory, ADT 2011, held in Piscataway, NJ, USA, in October 2011. The 24 revised full papers presented were carefully reviewed and selected from 50 submissions.

Formal decision and evaluation models are so widespread that almost no one can pretend not to have used or suffered the consequences of one of them. This book is a guide aimed at helping the analyst to choose a model and use it consistently. A sound analysis of techniques is proposed and the presentation can be extended to most decision and evaluation models as a "decision aiding methodology."

Algorithmic decision theory is a new interdisciplinary research area that aims to bring together researchers from di?erent ?elds such as decision theory, d- crete mathematics, theoretical computer science and arti?cial intelligence, in order to improve decision support in the presence of massive databases, com- natorial structures, partial and/or uncertain information and distributed, p- sibly interoperating, decision makers. Such problems arise in several real-world decision-making scenarios such as humanitarian logistics, epidemiology, risk assessment and management, e-government, electronic commerce, and rec- mender systems. In 2007, the EU-funded COST Action IC0602 on Algorithmic Decision T- ory was started, networking a number of researchers and research laboratories around Europe (and beyond). The COST Action IC0602 now gathers over 100 participants from more than 30 countries (including non-COST countries such as Australia, South Africa and the USA). For more details see www.algodec.org. Within the Action, and in cooperation with the EURO Working Group on Pr- erences, itwasdecidedtostartanewseriesofconferencesonalgorithmicdecision theory, the goal being to provide a forum for researchers interested in this area. This volume contains the papers presented at ADT 2009, the ?rst Inter- tional Conference on Algorithmic Decision Theory. The conference was held in SanServolo, a smallislandintheVenetianLagoon, onOctober20-23,2009.The programoftheconferenceincludedoralpresentations, posters, invitedtalks, and tutorials (for more information see www.adt2009

Formal decision and evaluation models are sets of explicit and well-defined rules to collect, assess, and process information in order to be able to make recommendations in decision and/or evaluation processes. They are so widespread that almost no one can pretend not to have used or suffered the consequences of one of them. Our earlier companion volume, Evaluation and Decision Models, heavily criticised formal models but also argued that they could be useful. On the other hand, Evaluation and Decision Models with Multiple Criteria is a guide aimed at helping the analyst to choose a model and use it consistently. We propose a sound analysis of techniques and our presentation can be extended to most decision and evaluation models as a decision aiding methodology. This volume is intended for the enlightened practitioner, for anyone who uses decision or evaluation models - for research or for applications - and is willing to question his practice, to have a deeper understanding of what he does.

The purpose of Evaluation and Decision Models: A Critical Perspective is to provide a critical thinking framework for all individuals utilizing decision and evaluation models, whether it be for research or applications. It is axiomatic that all evaluation and decision models suffer some limitations. There are situations where a decision model will not perform to expectations. This book argues that there is no best decision or evaluation model, but that decision-makers must understand the principles of formal evaluation and decision models and apply them critically. Hence, the book seeks to deepen our understanding of evaluation and decision models and encourage users of these models to think more analytically about them. The authors work in six different European universities. Their backgrounds are varied: mathematics, economics, engineering, law, and geology, and they teach in engineering, business, mathematics, computer science, and psychology in their universities. As a group, the authors have particular expertise in a variety of decision models that include preference modelling, fuzzy logic, aggregation techniques, social choice theory, artificial intelligence, problem structuring, measurement theory, operations research, and multiple criteria decision support. In addition to their decision analysis research, all the authors have been involved in a variety of high-impact applications which include software evaluation, location of a nuclear repository, the rehabilitation of a sewer network, and the location of high-voltage lines. It is this variety within the authorship that unifies this book into a systematic examination of how best formal decision models can be used. The monographis an excellent tool for researchers of decision analysis and decision-makers.

In the first volume of the set, Evaluation and Decision Models: A Critical Perspective, the purpose is to provide a critical thinking framework for all individuals utilizing decision and evaluation models, whether it be for research or applications. In the book, the authors criticized formal models while pointing out where these models can be useful. On the other hand, Evaluation and Decision Models with Multiple Criteria is a guide, a way of reasoning aimed at helping the analyst to choose a model and use it consistently. The authors propose, often using an axiomatic point of view, a sound analysis of techniques aimed at supporting the decision aiding process. The presentation is carried out within a unique framework that can be extended to most decision and evaluation models, as a "decision aiding methodology."