Algorithmic Decision Theory

Francesca Rossi, Alexis Tsoukias, “Algorithmic Decision Theory”
Springer 2009 | ISBN-10: 3642044271 | 460 Pages | PDF | 6,6 MB

Algorithmic Decision Theory is a new interdisciplinary research area that aims to put together researchers coming from different fields such as Decision Theory, Discrete Mathematics, Theoretical Computer Science and Artificial Intelligence, in order to improve decision support in the presence of massive data bases, combinatorial structures, partial and/or uncertain information and distributed, possibly 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 recommender systems

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 to preference modeling, from uncertainty to preference learning, from multi-criteria decision making to game theory.

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