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.org).
This volume contains the papers presented at ADT 2009, the first International Conference on Algorithmic Decision Theory. The conference was held in San Servolo, a small island of the Venice lagoon, during October 20-23, 2009. The program of the conference included oral presentations, posters, invited talks, and tutorials.
The conference received 65 submissions of which 39 papers were accepted (9 papers were posters). The topics of these papers range from computational social choice preference modeling, from uncertainty to preference learning, from multi-criteria decision making to game theory.