Fields of expertise
BiographyProfessor Faltings joined EPFL in 1987 as professor of Artificial Intelligence. He holds a PhD degree from the University of Illinois at Urbana-Champaign, and a diploma from the ETHZ. His research has spanned different areas of intelligent systems linked to model-based reasoning. In particular, he has contributed to qualitative spatial reasoning, case-based reasoning (especially for design problems), constraint satisfaction for design and logistics problems, multi-agent systems, and intelligent user interfaces. His current work is oriented towards multi-agent systems and social computing, using concepts of game theory, constraint optimization and machine learning. In 1999, Professor Faltings co-founded Iconomic Systems, a company that developed a new agent-based paradigm for travel e-commerce. He has since co-founded 5 other startup companies and advised several others. Prof. Faltings has published more than 150 refereed papers on his work, and participates regularly in program committees of all major conferences in the field. He has served as associate editor of of the major journals, including the Journal of Artificial Intelligence Research (JAIR) and the Artificial Intelligence Journal. From 1996 to 1998, he served as head of the computer science department.
Building INR 231
Tel. + 41 21 693 27 35
CURRENT WORKMulti-agent constraint optimization: we develop methods for optimizing the joint operation of multiple agents, taking into account considerations of communication complexity, uncertainty and privacy.
Truthful opinion polls: we develop game-theoretic methods to ensure that information provided by self-interested agents is truthful and accurate, in order to make the wisdom of the crowds more accurate.
Preference-based search (together with HCI group): we develop methods that allow people to find items that best satisfy their preferences in large collections of structured or semi-structured data. We consider scenarios ranging from recommender systems to search in databases using constraints.
Multi-agent learning: we consider systems where multiple agents learn from their own data sources, in scenarios such as wireless channel allocation, recommendation and reputation systems, and information security.
Boi Faltings' research is sponsored by the Swiss National Science Foundation, the Swiss Federal Commission for Technology Innovation (CTI), and the European Commission.
Incentives for Effort in Crowdsourcing using the Peer Truth SerumACM Transactions on Intelligent Systems and Technology. 2016. DOI : 10.1145/2856102.
Incentives to Counter Bias in Human Computation2014. p. 59-66.
Eliciting Truthful Information with the Peer Truth SerumThe 15th ACM conference on Economics and Computation (EC’14).
Incentive Mechanisms for Community SensingIeee Transactions On Computers. 2014. DOI : 10.1109/Tc.2013.150.
Eliciting Truthful Measurements from a Community of Sensors2012. p. 47-54.
Incentives for Answering Hypothetical Questions2011. Workshop on Social Computing and User Generated Content, EC-11.
Reporting incentives and biases in online review forumsACM Transactions on the Web (TWEB). 2010. DOI : 10.1145/1734200.1734202.
A Publish/Subscribe Approach to Processing Continuous Queries over Sensor StreamsLausanne, EPFL, 2010. DOI : 10.5075/epfl-thesis-4681.
Continuous Query Evaluation over Distributed Sensor Networks2010. 26th IEEE International Conference on Data Engineering (ICDE 2010), Long Beach, California, USA, March 1-6, 2010. p. 912-923.
Forward Error Correction for Multipath Media StreamingIEEE Transactions On Circuits And Systems For Video Technology. 2009. DOI : 10.1109/TCSVT.2009.2022800.
Mechanisms for Making Crowds TruthfulJournal Of Artificial Intelligence Research. 2009.
Rating aggregation in collaborative filtering systems2009. 3rd ACM conference on Recommender systems (RecSys 09), New York, New York, USA, 23-25 October 2009. p. 349-352. DOI : 10.1145/1639714.1639785.
Aggregating Reputation Feedback2009. 1st International Conference on Reputation: Theory and Technology, Gargonza, Italy, March 2009. p. 62-74.
Processing Publish/Subscribe Queries over Distributed Data Streams2009. DEBS 2009 3rd ACM International Conference on Distributed Event-Based Systems, Nashville, TN, July 6-9, 2009.
Truthful Opinions from the CrowdsACM SIGEcom Exchanges. 2008.
Incentives for Expressing Opinions in Online Polls2008. p. 119-128.
System and method for monitoring quality of serviceUS8843385 ; US2008137550 . 2008.
Query Driven Operator Placement for Complex Event Detection over Data Streams2008. 3rd IEEE European Conference on Smart Sensing and Context (EuroSSC), Zurich, Switzerland, October 29-31, 2008.
Distributed Media Rate Allocation in Multipath NetworksSignal Processing: Image Communications. 2008.
Understanding User Behavior in Online Feedback Reporting2007. p. 134-142.
Robust Incentive-Compatible Feedback PaymentsAgent-Mediated Electronic Commerce; Berlin Heidelberg: Springer-Verlag, 2007. p. 204-218.
Reporting Incentives in Online Feedback Forums: The Influence of Effort2007
Reliable QoS Monitoring Based on Client Feedback2007. p. 1003-1011.
Providing Cooperative Incentives through the Structure of Social Networks2007
Obtaining Reliable Feedback for Sanctioning Reputation MechanismsJournal of Artificial Intelligence Research (JAIR). 2007.
Incentive-compatible Online Opinion Polls2007
Governing Environments for Agent-based Traffic Simulations2007.
Collusion Resistant, Incentive Compatible Feedback Payments2007. p. 200-209.
Automated Dynamic Maintenance of Composite Services Based on Service Reputation2007. p. 449-455.
Automated Design of Prediction Market Pricing Functions2007
Truthful reputation mechanisms for online systemsLausanne, EPFL, 2007. DOI : 10.5075/epfl-thesis-3955.
Adaptive media streaming over multipath networksLausanne, EPFL, 2007. DOI : 10.5075/epfl-thesis-3908.
Joint Network and Rate Allocation for Video Streaming over Multiple Wireless Networks2007. IEEE International Symposium on Multimedia.
Joint Network and Rate Allocation for Simultaneous Wireless Applications2007. International Conference on Multimedia and Expo, Beijing, China, July 2007.
Enabling Adaptive Video Streaming in P2P SystemsIEEE Communications Magazine. 2007.
Packet Media Streaming with Imprecise Rate EstimationJournal on Advances in Multimedia, Hindawi Press. 2007.
Media Flow Rate Allocation in Multipath NetworksIEEE Transactions on Multimedia. 2007. DOI : 10.1109/TMM.2007.902852.
Packet Selection and Scheduling for Multipath Video StreamingIEEE Transactions on Multimedia. 2007.
Media-specific rate allocation in heterogeneous wireless networksJournal of Zhejiang University - Science A. 2006. DOI : 10.1631/jzus.2006.A0713.
Distributed Media Rate Allocation in Multipath Networks2006
Efficient Probabilistic Subsumption Checking for Content-Based Publish/Subscribe Systems2006. 7th International Middleware Conference (Middleware 2006), Melbourne, Australia, November 27 - December 1, 2006.
Minimum Payments that Reward Honest Reputation Feedback2006. p. 190-199.
Using CHI-Scores to Reward Honest Feedback from Repeated Interactions2006. p. 1233-1240.
Media-Specific Rate Allocation in Heterogeneous Wireless Networks2006.
Distributed Media Rate Allocation in Overlay Networks2006.
Media Streaming with Conservative Delay on Variable Rate Channels2006.
Community-Aware Event Dissemination2006
Fast Probabilistic Subsumption Checking for Publish/Subscribe Systems2006
Media-Specific Rate Allocation in Multipath Networks2005
Reputation-based Service Level Agreements for Web ServicesService Oriented Computing (ICSOC - 2005); 2005. p. 396-409.
Enforcing Truthful Strategies in Incentive Compatible Reputation MechanismsInternet and Network Economics; Springer Verlag, 2005. p. 268-277.
CONFESS: Eliciting Honest Feedback without Independent Verification AuthoritiesAgent-Mediated Electronic Commerce VI: AAMAS 2004 Workshop; Springer, 2005. p. 59-72.
Eliminating Undesired Equilibrium Points from Incentive Compatible Reputation Mechanisms2005.
Reputation-based Pricing of P2P Services2005.
Media Aware Routing in Large Scale Networks with Overlay2005.
Eliminating Undesired Equilibrium Points from Incentive Compatible Reputation Mechanisms2005
Eliciting Truthful Feedback for Binary Reputation Mechanisms2004. p. 214-220.
"CONFESS". An Incentive Compatible Reputation Mechanism for the Online Hotel Booking Industry.2004. p. 205-212.
Distortion Optimized Multipath Video Streaming2004.
Optimal FEC Rate for Media Streaming in Active Networks2004. p. 1319-1322.
Packet Selection and Scheduling for Multipath Video Streaming2004
Joint Synchronization, Routing and Energy Saving in Multi-hop Hybrid Networks2004
Joint Synchronization, Routing and Energy Saving in CSMA/CA Multi-Hop Hybrid Networks2004. 1st IEEE International Conference on Mobile Ad-hoc and Sensor Systems MASS 2004, Fort Lauderdale, Florida, USA. p. 10.
An Incentive Compatible Reputation Mechanism2003. p. 285-292.
Towards Incentive-Compatible Reputation ManagementTrust, Reputation and Security: Theories and Practice; Springer-Verlag, 2003. p. 138-147.
|R. Jurca and B. Faltings
Journal of Artificial Intelligence Research (JAIR), 34, 2009, pp. 209-253.
|Mechanisms for Making Crowds Truthful|
|R. Jurca and B. Faltings
Proceeddings of the 2008 ACM Conference on Electronic Commerce, July, 2008, pp. 119-128
|Truthful Opinions from the Crowds|
|A. Petcu and B. Faltings
Proceedings of the 20th International Joint Conference on Artificial Intelligence, IJCAI-07, Hyderabad, India, Jan, 2007, pp. 1452-1457
|MB-DPOP: A New Memory-Bounded Algorithm for Distributed Optimization|
|P. Viappiani, B. Faltings and P. Pu
Journal of Artificial Intelligence Research (JAIR), 27, 2006, pp. 465-503
|Preference-based Search using Example-Critiquing with Suggestions|
In Handbook of Constraint Programming, Foundations of Artificial Intelligence, Francesca Rossi, Peter van Beek, Toby Walsh (ed.), 2006, pp. 699-729
|Distributed Constraint Programming|
|C. Frei, B. Faltings, and M. Hamdi
IEEE Journal on Selected Areas in Communication, 23(2), February, 2005, pp. 304-320
|Resource Allocation in Communication Networks Using Abstraction and Constraint Satisfaction|
|B. Faltings and S. Macho-Gonzalez
Artificial Intelligence, 161 (1-2), January, 2005, pp. 181-208
|Open Constraint Programming|
Teaching & PhD