Orchid Project

@article{
  orchid250,
  volume = {230},
  month = {January},
  title = {A hybrid exact algorithm for complete set partitioning},
  author = {Tomasz Michalak and Talal Rahwan and Edith Elkind and Michael Wooldridge and Nicholas R Jennings},
  year = {2016},
  pages = {14--50},
  journal = {Artificial Intelligence},
  keywords = {Mechanism Design, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/250/1/1-s2.0-S0004370215001198-main.pdf} }

@inproceedings{
  orchid260,
  booktitle = {AAMAS 16: 15th Int. Conf. on Autonomous Agents and Multi-Agent Systems},
  title = {Online planning for collaborative search and rescue by heterogeneous robot teams},
  author = {Z Beck and W L Teacy and Alex Rogers and Nicholas R Jennings},
  year = {2016},
keywords = {Human-Agent Interaction, Human-Robot Interaction, Mechanism Design, Machine Learning, Applications, Agile Teaming, Incentive Engineering} }

@article{
  orchid251,
  title = {Human-agent collaboration for disaster response },
  author = {Sarvapali D Ramchurn and Feng Wu and J.E. Fischer and Steven Reece and W Jiang and Stephen J Roberts and T Rodden and Nicholas R Jennings},
  year = {2016},
  pages = {1--30},
  journal = {Journal of Autonomous Agents and Multi-Agent Systems},
keywords = {Disaster Recovery, Human-Agent Interaction, Accountable Information Infrastructure, Applications, Agile Teaming, Flexible Autonomy, Incentive Engineering} }

@inproceedings{
  orchid257,
  booktitle = {AAMAS 16: 15th Int. Conf. on Autonomous Agents and Multi-Agent Systems},
  title = {Bid2Charge: Market user interface design for electric vehicle charging},
  author = {Sebastian Stein and Enrico H Gerding and A Nadea and Avi Rosenfeld and Nicholas R Jennings},
  year = {2016},
keywords = {Energy Management, Human-Agent Interaction, Applications, Incentive Engineering} }

@inproceedings{
  orchid259,
  booktitle = {AAMAS 16: 15th Int. Conf. on Autonomous Agents and Multi-Agent Systems},
  title = {Playing repeated security games with no prior knowledge},
  author = {Long Tran-Thanh and H Xu},
  year = {2016},
keywords = {Human-Agent Interaction, Mechanism Design, Machine Learning, Incentive Engineering} }

@inproceedings{
  orchid258,
  booktitle = {AAMAS 16: 15th Int. Conf. on Autonomous Agents and Multi-Agent Systems},
  title = {Fault tolerant mechanism design for general task allocation},
  author = {D Zhao and Sarvapali D Ramchurn and Nicholas R Jennings},
  year = {2016},
keywords = {Mechanism Design, Applications, Incentive Engineering} }

@article{
  orchid252,
  title = {Intention-aware routing of electric vehicles },
  author = {M de Weerdt and Sebastian Stein and Enrico H Gerding and Valentin Robu and Nicholas R Jennings},
  year = {2016},
  pages = {1--11},
  journal = {IEEE Transactions on Intelligent Transportation Systems},
keywords = {Energy Management, Mechanism Design, Machine Learning, Incentive Engineering} }

@inproceedings{
  orchid220,
  booktitle = {AAAI-15: Twenty-Ninth Conference on Artificial Intelligence},
  title = {Sharing Rides with Friends: a Coalition Formation Algorithm for Ridesharing},
  author = {Filippo Bistaffa and Alessandro Farinelli and Sarvapali D Ramchurn},
  year = {2015},
  keywords = {Energy Management, Mechanism Design, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/220/1/aaai2015.pdf} }

@article{
  orchid234,
  volume = {6},
  number = {1},
  title = {Modelling the thermal dynamics of buildings: a latent force model based approach},
  author = {Siddhartha Ghosh and Steven Reece and Alex Rogers and Stephen J Roberts and Areej Malibari and Nicholas R Jennings},
  year = {2015},
  pages = {1--27},
  journal = {ACM Transactions on Intelligent Systems and Technology},
  keywords = {Energy Management, Mechanism Design, Machine Learning, Agile Teaming, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/234/1/Modelling%2520the%2520Thermal%2520Dynamics%2520of%2520Buildings%2520-%2520A%2520Latent%2520Force%2520Model%2520Based%2520Approach.pdf} }

@article{
  orchid216,
  volume = {11},
  number = {99},
  title = {Crowdsourcing contest dilemma},
  author = {Victor Naroditskiy and Nicholas R Jennings and Pascal Van Hentenryck and Manuel Cebrian},
  year = {2015},
  journal = {Journal of The Royal Society Interface},
  keywords = {Crowd-sourcing, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/216/1/20140532.full.pdf} }

@inproceedings{
  orchid217,
  booktitle = {AAAI-15: Twenty-Ninth Conference on Artificial Intelligence},
  title = {On the convergence of iterative voting: how restrictive should restricted dynamics be?},
  author = {Svetlana Obraztsova and Evangelos Markakis and Maria Polukarov and Zinovi Rabinovich and Nicholas R Jennings},
  year = {2015},
  keywords = {Mechanism Design, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/217/1/aaai15-restricted-dynamics.pdf} }

@inproceedings{
  orchid235,
  booktitle = {IJCAI 15},
  title = {Convergence to Equilibria in Strategic Candidacy},
  author = {Maria Polukarov and Svetlana Obraztsova and Zinovi Rabinovich and Alexander Kruglyi and Nicholas R Jennings},
  year = {2015},
  keywords = {Mechanism Design, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/235/1/DCmainCameraReady.pdf} }

@inproceedings{
  orchid230,
  booktitle = {AAMAS-15 : 14th Int. Conf. on Autonomous Agents and Multi-Agent Systems },
  title = {HAC-ER: A disaster response system based on human-agent collectives},
  author = {Sarvapali D Ramchurn and Edwin Simpson and J.E. Fischer and T. Dong Huynh and Yuki Ikuno and Steven Reece and W Jiang and Feng Wu and J Flann and Stephen J Roberts and T Rodden and Nicholas R Jennings},
  year = {2015},
keywords = {Disaster Recovery, Human-Agent Interaction, Accountable Information Infrastructure, Applications, Agile Teaming, Flexible Autonomy, Incentive Engineering} }

@inproceedings{
  orchid236,
  booktitle = {WWW 15},
  title = {Language Understanding in the Wild: Combining Crowdsourcing and Machine Learning},
  author = {Edwin Simpson and Matteo Venanzi and Steven Reece and Pushmeet Kohli and John Guiver and Stephen J Roberts and Nicholas R Jennings},
  year = {2015},
  pages = {992--1002},
  keywords = {Crowd-sourcing, Machine Learning, Applications, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/236/1/WWW15-BCCWords.pdf} }

@inproceedings{
  orchid219,
  booktitle = {AAAI-15: Twenty-Ninth Conference on Artificial Intelligence},
  title = {Crowdsourcing Complex Workflows under Budget Constraints },
  author = {Long Tran-Thanh and T. Dong Huynh and Avi Rosenfeld and Sarvapali D Ramchurn and Nicholas R Jennings},
  year = {2015},
  keywords = {Crowd-sourcing, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/219/1/aaai15-budgetfix.pdf} }

@inproceedings{
  orchid237,
  booktitle = {IJCAI 15},
  title = {Efficient Algorithms with performance guarantees for the stochastic multiple-choice knapsack problem},
  author = {Long Tran-Thanh and Yingce Xia and Tao Qin and Nicholas R Jennings},
  year = {2015},
  keywords = {Mechanism Design, Machine Learning, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/237/1/stochastic%5fknapsak%5fijcai15%5ffinal.pdf} }

@inproceedings{
  orchid238,
  booktitle = {IJCAI 15},
  title = {Bayesian modelling of community-based multidimensional trust in participatory sensing under data sparsity},
  author = {Matteo Venanzi and W L Teacy and Alex Rogers and Nicholas R Jennings},
  year = {2015},
  pages = {717--724},
  keywords = {Mechanism Design, Trust and Reputation, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/238/1/ijcai2015%5fbace.pdf} }

@inproceedings{
  orchid239,
  booktitle = {IJCAI 15},
  title = {Agile Planning for Real-World Disaster Response.},
  author = {Feng Wu and Sarvapali D Ramchurn and W Jiang and J.E. Fischer and T Rodden and Nicholas R Jennings},
  year = {2015},
  keywords = {Agent-based Computing, Disaster Recovery, Mechanism Design, Applications, Agile Teaming, Flexible Autonomy, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/239/1/main.pdf} }

@inproceedings{
  orchid202,
  booktitle = {COIN 2014: The 17th International Workshop on Coordination, Organisations, Institutions and Norms },
  title = {The cost of interference in evolving systems.},
  author = {TheAnh Han and Long Tran-Thanh and Nicholas R Jennings},
  year = {2014},
  keywords = {Mechanism Design, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/202/1/investment%5fin%5fEG.pdf} }

@article{
  orchid198,
  title = {On human-agent collectives},
  author = {Nicholas R Jennings and Luc Moreau and David Nicholson and Sarvapali D Ramchurn and Stephen J Roberts and T Rodden and Alex Rogers},
  year = {2014},
  journal = {Communications of the ACM },
  keywords = {Agent-based Computing, Crowd-sourcing, Disaster Recovery, Energy Management, Human Computation, Provenance, Ubiquitous Computing, Accountable Information Infrastructure, Applications, Agile Teaming, Flexible Autonomy, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/198/1/CACM%2520HAC%2520ARTICLE%2520%2520final.pdf} }

@inproceedings{
  orchid231,
  booktitle = {ICICA-2014},
  title = {Predicting Economic Indicators from Web Text Using Sentiment Composition},
  author = {A Levenberg and S Pulman and K Moilanen and Edwin Simpson and Stephen J Roberts},
  year = {2014},
  keywords = {Crowd-sourcing, Machine Learning, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/231/1/sentiment%5fICICA2014.pdf} }

@article{
  orchid232,
  volume = {3},
  number = {2},
  title = {Predicting Economic Indicators from Web Text Using Sentiment Composition},
  author = {A Levenberg and S Pulman and K Moilanen and Edwin Simpson and Stephen J Roberts},
  year = {2014},
  pages = {109--115},
  journal = {International Journal of Computer and Communication Engineering},
keywords = {Crowd-sourcing, Machine Learning, Incentive Engineering} }

@inproceedings{
  orchid207,
  booktitle = {HCOMP2014: Conference on Human Computation & Crowdsourcing},
  title = {Referral incentives in crowdfunding },
  author = {Victor Naroditskiy and Sebastian Stein and Long Tran-Thanh and Michael Vlassopoulos and Nicholas R Jennings},
  year = {2014},
  keywords = {Crowd-sourcing, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/207/1/referrals.pdf} }

@article{
  orchid196,
  title = {Efficient state-space inference of periodic latent force models. },
  author = {Steven Reece and Stephen J Roberts and Siddhartha Ghosh and Alex Rogers and Nicholas R Jennings},
  year = {2014},
  pages = {1--66},
  journal = {Journal of Machine Learning Research},
  keywords = {Machine Learning, Agile Teaming, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/196/1/reece14.pdf} }

@inproceedings{
  orchid172,
  booktitle = {13th Int. Conf. on Autonomous Agents and Multi-Agent Systems},
  title = {BudgetFix: Budget limited crowdsourcing for interdependent task allocation with quality guarantees},
  author = {Long Tran-Thanh and T. Dong Huynh and Avi Rosenfeld and Sarvapali D Ramchurn and Nicholas R Jennings},
  year = {2014},
  pages = {477--484},
  keywords = {Crowd-sourcing, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/172/1/fp531%5fTran-Thanh.pdf} }

@inproceedings{
  orchid209,
  booktitle = {23rd International World Wide Web Conference (WWW)},
  title = {Community-Based Bayesian Aggregation Models for Crowdsourcing},
  author = {Matteo Venanzi and John Guiver and Gabriella Kazai and Pushmeet Kohli and Milad Shokouhi},
  year = {2014},
  keywords = {Crowd-sourcing, Applications, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/209/1/vkgsk%5fwww2014.pdf} }

@article{
  orchid89,
  title = {Destroy to Save.},
  author = {Geoffroy de Clippel and Victor Naroditskiy and Maria Polukarov and Amy Greenwald and Nicholas R Jennings},
  year = {2014},
  pages = {1--13},
  journal = {Games and Economic Behavior},
  keywords = {Mechanism Design, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/89/1/main.pdf} }

@article{
  orchid168,
  month = {August},
  title = {Maritime Abnormality Detection using Gaussian Processes },
  author = {M. Smith and Steven Reece and I Rezek and Ioannis Psorakis and Stephen J Roberts},
  year = {2013},
  pages = {1--26},
  journal = {Knowledge and Information Systems},
  keywords = {Machine Learning, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/168/1/art%253A10.1007%252Fs10115-013-0685-z.pdf} }

@inproceedings{
  orchid149,
  booktitle = {Conference on Uncertainty in Artificial Intelligence (UAI)},
  month = {July},
  title = {Learning periodic human behaviour models from sparse data for crowdsourcing aid delivery in developing countries},
  author = {James McInerney and Alex Rogers and Nicholas R Jennings},
  year = {2013},
  pages = {401--410},
  keywords = {Crowd-sourcing, Applications, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/149/1/uai.pdf} }

@inproceedings{
  orchid93,
  booktitle = {12th Int. Conf on Autonomous Agents and Multi-Agent Systems},
  title = {Matching games with compact externalities},
  author = {S Branzei and Tomasz Michalak and Talal Rahwan and Kate Larson and Nicholas R Jennings},
  year = {2013},
  pages = {295--302},
  keywords = {Mechanism Design, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/93/1/fp22-branzei.pdf} }

@inproceedings{
  orchid164,
  booktitle = {Novel Methods for Learning and Optimization of Control Policies and Trajectories for Robotics, ICRA, 2013.},
  title = {Nonlinear adaptive hybrid control by combining Gaussian process system identification with classical control laws},
  author = {Jan-P Calliess and Michael A Osborne and Stephen J Roberts},
  year = {2013},
  keywords = {Machine Learning, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/164/1/Callies.pdf} }

@inproceedings{
  orchid165,
  booktitle = {Advances in Machine Learning for Sensorimotor Control, NIPS, 2013.},
  title = {Stochastic processes and feedback-linearisation for online identification and Bayesian adaptive control of fully actuated mechanical systems},
  author = {Jan-P Calliess and Antonis Papachristodoulou and Stephen J Roberts},
  year = {2013},
  keywords = {Machine Learning, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/165/1/1311.4468v1.pdf} }

@inproceedings{
  orchid163,
  booktitle = {SoCS 2013: The Sixth Annual Symposium on Combinatorial Search },
  title = {Multi-agent planning with mixed-integer programming and adaptive interaction constraint generation},
  author = {Jan-P Calliess and Stephen J Roberts},
  year = {2013},
  keywords = {Agent-based Computing, Mechanism Design, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/163/1/7258-30179-1-PB.pdf} }

@inproceedings{
  orchid147,
  booktitle = {6th International Symposium on Algorithmic Game Theory (SAGT) },
  title = {Cooperative Equilibria in Iterated Social Dilemmas.},
  author = {Valerio Capraro and Matteo Venanzi and Maria Polukarov and Nicholas R Jennings},
  year = {2013},
  pages = {146--158},
  keywords = {Mechanism Design, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/147/1/IteratedCooperativeEquilibriumSAGT.pdf} }

@incollection{
  orchid145,
  booktitle = {Multiagent Systems},
  title = {Computational Coalition Formation},
  author = {Edith Elkind and Talal Rahwan and Nicholas R Jennings},
  publisher = {MIT Press},
  year = {2013},
  pages = {329--380},
  keywords = {Machine Learning, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/145/1/weiss%5fMAS%5fBOOK%5fchapter08.pdf} }

@article{
  orchid178,
  volume = {10},
  number = {4},
  title = {Bus, bike and random journeys: crowdsourcing aid distribution in Ivory Coast},
  author = {James McInerney and Alex Rogers and Nicholas R Jennings},
  year = {2013},
  pages = {4--9},
  journal = {Significance},
  keywords = {Crowd-sourcing, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/178/1/j.1740-9713.2013.00673.x.pdf} }

@article{
  orchid143,
  volume = {46},
  title = {Efficient computation of the Shapley value for game-theoretic network centrality. },
  author = {Tomasz Michalak and K.V. Aaditha and Piotr Szczepanski and B. Ravindran and Nicholas R Jennings},
  year = {2013},
  pages = {607--650},
  journal = {Journal of AI Research},
  keywords = {Mechanism Design, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/143/1/Michalak%5fet%5fal%5fJAIR%5fv08.pdf} }

@inproceedings{
  orchid94,
  booktitle = {12th Int. Conf on Autonomous Agents and Multi-Agent Systems},
  title = {Redistribution in online mechanisms},
  author = {Victor Naroditskiy and Sofia Ceppi and Valentin Robu and Nicholas R Jennings},
  year = {2013},
  pages = {651--658},
  keywords = {Mechanism Design, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/94/1/paper.dvi%20-%20online.pdf} }

@article{
  orchid47,
  volume = {1},
  number = {1},
  title = {Optimal payments in dominant-strategy mechanisms for single-parameter domains.},
  author = {Victor Naroditskiy and Maria Polukarov and Nicholas R Jennings},
  year = {2013},
  pages = {4.1--4.21},
  journal = {ACM Transactions on Economics and Computation},
  keywords = {Mechanism Design, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/47/1/optimal%20payments.pdf} }

@article{
  orchid91,
  volume = {195},
  title = {Computing pure Bayesian-Nash equilibria in games with finite actions and continuous types},
  author = {Zinovi Rabinovich and Victor Naroditskiy and Enrico H Gerding and Nicholas R Jennings},
  year = {2013},
  pages = {106--139},
  journal = {Artificial Intelligence},
  keywords = {Mechanism Design, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/91/1/documentnew.pdf} }

@article{
  orchid84,
  volume = {46},
  number = {4},
  title = {Global manhunt pushes the limits of social mobilization.},
  author = {Iyad Rahwan and Sohan Dsouza and Alex Rutherford and Victor Naroditskiy and James McInerney and Matteo Venanzi and Nicholas R Jennings and Manuel Cebrian},
  year = {2013},
  pages = {68--75},
  journal = {IEEE Computer},
  keywords = {Crowd-sourcing, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/84/1/CO%5fCOM-2012-07-0132%5fRahwan.pdf} }

@article{
  orchid156,
  title = {Targeted social mobilization in a global manhunt},
  author = {Alex Rutherford and Manuel Cebrian and Iyad Rahwan and Sohan Dsouza and James McInerney and Victor Naroditskiy and Matteo Venanzi and Nicholas R Jennings and J.R. de Lara and Eero Wahlstedt and Steven.U. Miller},
  year = {2013},
  journal = {PLoS ONE},
keywords = {Crowd-sourcing, Incentive Engineering} }

@inproceedings{
  orchid167,
  booktitle = {the Twenty-First Text REtrieval Conference (TREC 2012)},
  title = {Using a Bayesian Model to Combine LDA Features with Crowdsourced Responses },
  author = {Edwin Simpson and Steven Reece and Antonio Penta and Sarvapali D Ramchurn},
  year = {2013},
  keywords = {Crowd-sourcing, Mechanism Design, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/167/1/HAC.crowd.final.pdf} }

@inproceedings{
  orchid121,
  booktitle = {NIPS-2012 workshop on Human Computation for Science and Sustainability},
  title = {Dynamic Bayesian Combination of Multiple Imperfect Classifiers},
  author = {Edwin Simpson and Stephen J Roberts and Arfon Smith},
  year = {2013},
keywords = {Mechanism Design, Machine Learning, Incentive Engineering} }

@inproceedings{
  orchid92,
  booktitle = {12th Int. Conf on Autonomous Agents and Multi-Agent Systems},
  title = {Efficient budget allocation with accuracy guarantees for crowdsourcing classification tasks},
  author = {Long Tran-Thanh and Matteo Venanzi and Alex Rogers and Nicholas R Jennings},
  year = {2013},
  pages = {901--908},
  keywords = {Crowd-sourcing, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/92/1/crowdverify%5ffinal.pdf} }

@inproceedings{
  orchid96,
  booktitle = {12th Int. Conf on Autonomous Agents and Multi-Agent Systems},
  title = {Taxation and stability in cooperative games},
  author = {Yair Zick and Maria Polukarov and Nicholas R Jennings},
  year = {2013},
  pages = {523--530},
  keywords = {Mechanism Design, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/96/1/main.pdf} }

@inproceedings{
  orchid142,
  booktitle = {23rd Int. Joint Conf. on AI (IJCAI)},
  title = {A Hidden Markov Model-Based Acoustic Cicada Detector for Crowdsourced Smartphone Biodiversity Monitoring},
  author = {Davide Zilli and Oliver Parson and Geoff V. Merrett and Alex Rogers},
  year = {2013},
  keywords = {Crowd-sourcing, Mechanism Design, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/142/1/NFC-IJCAI13.pdf} }

@incollection{
  orchid125,
  month = {November},
  author = {David Nicholson and Steven Reece and Alex Rogers and Stephen J Roberts and Nicholas R Jennings},
  booktitle = {Distributed Data Fusion for Network-Centric Operations},
  editor = {D Hall and C-Y Chong and J Llinas and M Liggins},
  title = {Distributed Data Fusion Design: Overarching Design Concerns and Some New Approaches},
  publisher = {CRC Press},
  pages = {17--46},
  year = {2012},
keywords = {Mechanism Design, Incentive Engineering} }

@article{
  orchid83,
  month = {October},
  title = {Verification in referral-based crowdsourcing. },
  author = {Victor Naroditskiy and Iyad Rahwan and Manuel Cebrian and Nicholas R Jennings},
  year = {2012},
  journal = {PLoS ONE },
  keywords = {Crowd-sourcing, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/83/1/journal.pone.0045924.pdf} }

@inproceedings{
  orchid70,
  booktitle = {in 15th International IEEE Conference on Intelligent Transportation Systems (ITSC-12)},
  month = {September},
  title = {Can priors be trusted? Learning to anticipate roadworks},
  author = {B Mathibela and Michael A Osborne and I Posner and P.M. Newman},
  year = {2012},
  keywords = {Machine Learning, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/70/1/roadworks%5f2012.pdf} }

@inproceedings{
  orchid60,
  booktitle = {the Fifteenth International Conference on Artificial Intelligence and Statistics (AISTATS 2012)},
  month = {April},
  title = {Bayesian quadrature for ratios},
  author = {Michael A Osborne and R Garnett and Stephen J Roberts and C Hart and S Aigrain and N.P. Gibson},
  year = {2012},
  journal = {the Fifteenth International Conference on Artificial Intelligence and Statistics (AISTATS 2012)},
  keywords = {Machine Learning, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/60/1/BQ%5faistats%5fappendix.pdf} }

@article{
  orchid79,
  title = {Towards optimization-based multi-agent collision-avoidance under continuous stochastic dynamics. },
  author = {Jan-P Calliess and Michael A Osborne and Stephen J Roberts},
  publisher = {AAAI},
  year = {2012},
  journal = {Proceedings of the AAAI-12 Workshop on Multiagent Pathfinding. },
  keywords = {Mechanism Design, Machine Learning, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/79/1/Towards%20Optimization-Based%20Multi-Agent%20Collision-Avoidance%20under%20Continuous%20Stochastic%20Dynamics%20-%20TowardsOptimization.pdf} }

@inproceedings{
  orchid53,
  booktitle = {Twenty-Sixth Conference on Artificial Intelligence (AAAI-12)},
  title = {Optimizing payments in dominant-strategy mechanisms for multi-parameter domains.},
  author = {Lachlan Dufton and Victor Naroditskiy and Maria Polukarov and Nicholas R Jennings},
  year = {2012},
  keywords = {Mechanism Design, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/53/1/mainpreprint.pdf} }

@article{
  orchid80,
  title = {Chance Constrained Model Predictive Control for Multi-Agent Systems with Coupling Constraints.},
  author = {D Lyons and Jan-P Calliess and U.D. Hanebeck},
  year = {2012},
  journal = {Proc. of American Control Conference (ACC' 2012) },
keywords = {Machine Learning, Incentive Engineering} }

@inproceedings{
  orchid85,
  booktitle = {The 8th Workshop on Internet & Network Economics },
  title = {Redistribution of VCG Payments in Public Project Problems},
  author = {Victor Naroditskiy and M Guo and Lachlan Dufton and Maria Polukarov and Nicholas R Jennings},
  year = {2012},
  keywords = {Mechanism Design, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/85/1/pg.pdf} }

@inproceedings{
  orchid58,
  booktitle = {Twenty-Sixth AAAI Conference on Artificial Intelligence (AAAI-12)},
  title = {Prediction and fault detection of environmental signals with uncharacterised faults.},
  author = {Michael A Osborne and R Garnett and K Swersky and N de Freitas },
  year = {2012},
  keywords = {Machine Learning, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/58/1/Osborne%5fGarnett%5fSwersky%5fde%5fFreitas%5ffault%5fbucket%5faaai%5f2012.pdf} }

@article{
  orchid11,
  volume = {9},
  number = {1},
  title = {Real-Time Information Processing of Environmental Sensor Network Data},
  author = {Michael A Osborne and Stephen J Roberts and Alex Rogers and Nicholas R Jennings},
  year = {2012},
  journal = {ACM Transactions on Sensor Networks},
  keywords = {Agent-based Computing, Applications, Incentive Engineering},
  howpublished = {http://www.orchid.ac.uk/eprints/11/1/tosn%5fgp%5frevised.pdf},
abstract = {In this paper, we consider the problem faced by a sensor network operator who must infer, in real-time, the value of some environmental parameter that is being monitored at discrete points in space and time by a sensor network. We describe a powerful and generic approach built upon an efficient multi-output Gaussian process that facilitates this information acquisition and processing. Our algorithm allows effective inference even with minimal domain knowledge, and we further introduce a formulation of Bayesian Monte Carlo to permit the principled management of the hyperparameters introduced by our flexible models. We demonstrate how our methods can be applied in cases where the data is delayed, intermittently missing, censored and/or correlated. We validate our approach using data collected from three networks of weather sensors and show that it yields better inference performance than both conventional independent Gaussian processes and the Kalman filter. Finally, we show that our formalism efficiently re-uses previous computations by following an online update procedure as new data sequentially arrives, and that this results in a four-fold increase in computational speed in the largest cases considered.} }

@article{
  orchid59,
  title = {Inferring social network structure in ecological systems from spatio-temporal data streams },
  author = {Ioannis Psorakis and Stephen J Roberts and I Rezek and Ben Sheldon},
  year = {2012},
  journal = {Journal of the Royal Society, Interface},
  keywords = {Mechanism Design, Machine Learning, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/59/1/psorakis%5frsi.pdf} }

@article{
  orchid77,
  title = {Gaussian Processes for Timeseries Modelling.},
  author = {Stephen J Roberts and Michael A Osborne and Mark Ebden and Steven Reece and N.P. Gibson and S Aigrain},
  year = {2012},
  journal = {Philosophical Transactions of the Royal Society A.},
  keywords = {Machine Learning, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/77/1/philTransA%5f2012.pdf} }

@inproceedings{
  orchid124,
  booktitle = {Human Computation for Science and Computational Sustainability Workshop, Neural Information Processing Systems (NIPS 2012)},
  title = {An Information Theoretic Approach to Managing Multiple Decision Makers},
  author = {Edwin Simpson and Steven Reece and Sarvapali D Ramchurn and Stephen J Roberts},
  year = {2012},
keywords = {Machine Learning, Incentive Engineering} }

@incollection{
  orchid32,
  booktitle = {Decision Making with Imperfect Decision Makers},
  title = {Dynamic Bayesian Combination of Multiple Imperfect Classifiers},
  author = {Edwin Simpson and Stephen J Roberts and Ioannis Psorakis and Chris Lintott},
  publisher = {Springer},
  year = {2012},
  series = {Intelligient Systems Reference Library},
  keywords = {Machine Learning, Applications, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/32/1/galaxyZooSN%5fsimpson%5fetal.pdf} }

@inproceedings{
  orchid122,
  booktitle = {IEEE International Conference on Data Mining},
  title = {Online Maritime Abnormality Detection using Gaussian Processes and Extreme Value Theory},
  author = {M. Smith and Steven Reece and Stephen J Roberts and I Rezek},
  year = {2012},
  keywords = {Mechanism Design, Machine Learning, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/122/1/OnlineGaussianProcessEVT.pdf} }

@article{
  orchid28,
  title = {A model-based online mechanism with pre-commitment and its application to electric vehicle charging},
  author = {Sebastian Stein and Enrico H Gerding and Valentin Robu and Nicholas R Jennings},
  publisher = {AAMAS},
  year = {2012},
  journal = {Proc. 11th Int. Conference on Autonomous Agents and Multi-Agent Systems,},
  keywords = {Mechanism Design, Applications, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/28/1/camera%5fready%5ffinal.pdf} }

@article{
  orchid26,
  title = {Decentralised channel allocation and information sharing for teams of cooperative agents},
  author = {Sebastian Stein and S Williamson and Nicholas R Jennings},
  publisher = {AAMAS},
  year = {2012},
  journal = {Proc. 11th Int. Conference on Autonomous Agents and Multi-Agent Systems,},
  keywords = {Decentralised Control, Applications, Agile Teaming, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/26/1/camera%5fready%5ffinal.pdf} }

@inproceedings{
  orchid50,
  booktitle = {, Twenty-Sixth AAAI Conference on Artificial Intelligence (AAAI-12)},
  title = {Knapsack based optimal policies for budget-limited multi-armed bandits.},
  author = {Long Tran-Thanh and Archie C Chapman and Alex Rogers and Nicholas R Jennings},
  year = {2012},
  keywords = {Mechanism Design, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/50/1/LTT%5fAAAI2012%5fBandit%5ffinalversion.pdf} }

@article{
  orchid12,
  volume = {25},
  number = {2},
  title = {Long?Term Information Collection with Energy Harvesting Wireless Sensors: A Multi?Armed Bandit Based Approac},
  author = {Long Tran-Thanh and Alex Rogers and Nicholas R Jennings},
  year = {2012},
  pages = {352--394},
  journal = {Journal of Autonomous Agents and Multi-agent Systems},
  keywords = {Agent-based Computing, Applications, Incentive Engineering},
  howpublished = {http://www.orchid.ac.uk/eprints/12/1/LTT%5fJAAMAS2010.pdf},
abstract = {This paper reports on the development of a multi?agent approach to long-term information collection in networks of energy harvesting wireless sensors. In particular, we focus on developing energy management and data routing policies that adapt their behaviour according to the energy that is harvested, in order to maximise the amount of information collected given the available energy budget. In so doing, we introduce a new energy management technique, based on multi?armed bandit learning, that allows each agent to adaptively allocate its energy budget across the tasks of data sampling, receiving and transmitting. By using this approach, each agent can learn the optimal energy budget settings that give it efficient information collection in the long run. Then, we propose two novel decentralised multi?hop algorithms for data routing. The first proveably maximises the information throughput in the network, but can sometimes involve high communication cost. The second algorithm provides near?optimal performance, but with reduced computational and communication costs. Finally, we demonstrate that, by using our approaches for energy management and routing, we can achieve a 120% improvement in long term information collection against state?of?the?art benchmarks.} }

@article{
  orchid86,
  volume = {45},
  title = {Coalition structure generation over graphs.},
  author = {Thomas Voice and Maria Polukarov and Nicholas R Jennings},
  year = {2012},
  pages = {165--196},
  journal = {Journal of Artificial Intelligence Research},
  keywords = {Mechanism Design, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/86/1/voice12a.pdf} }

@article{
  orchid15,
  month = {December},
  title = {Budget-Balanced and Nearly Efficient Randomized Mechanisms: Public Goods and Beyond},
  author = {M Guo and Victor Naroditskiy and V Conitzer and Amy Greenwald and Nicholas R Jennings},
  year = {2011},
  journal = {Proc. of the 7th Workshop on Internet and Network Economics},
  keywords = {Mechanism Design, Incentive Engineering},
  howpublished = {http://www.orchid.ac.uk/eprints/15/1/paper%5f73.pdf},
abstract = {Many scenarios where participants hold private information require payments to encourage truthful revelation. Some of these scenarios have no natural residual claimant who would absorb the budget surplus or cover the deficit. Faltings proposed the idea of excluding one agent uniformly at random and making him the residual claimant. Based on this idea, we propose two classes of public good mechanisms and derive optimal ones within each class: Faltings' mechanism is optimal in one of the classes. We then move on to general mechanism design settings, where we prove guarantees on the social welfare achieved by Faltings' mechanism. Finally, we analyze a modification of the mechanism where budget balance is achieved without designating any agent as the residual claimant.} }

@inproceedings{
  orchid7,
  month = {December},
  author = {Edwin Simpson and Stephen J Roberts and Arfon Smith and Chris Lintott},
  booktitle = {NIPS 2011},
  address = {Oxford},
  title = {Bayesian Combination of Multiple, Imperfect Classifiers},
  publisher = {University of Oxford},
  pages = {1--8},
  year = {2011},
  keywords = {Machine Learning, Applications, Incentive Engineering},
  howpublished = {http://www.orchid.ac.uk/eprints/7/1/vbibcc%5fworkshop.pdf},
abstract = {Classifier combination methods need to make best use of the outputs of multiple, imperfect classifiers to enable higher accuracy classifications. In many situations, such as when human decisions need to be combined, the base decisions can vary enormously in reliability. A Bayesian approach to such uncertain combination allows us to infer the differences in performance between individuals and to incorporate any available prior knowledge about their abilities when training data is sparse. In this paper we explore Bayesian classifier combination, using the computationally efficient framework of variational Bayesian inference. We apply the approach to real data from a large citizen science project, Galaxy Zoo Supernovae, and show that our method far outperforms other established approaches to imperfect decision combination. We go on to analyse the putative community structure of the decision makers, based on their inferred decision making strategies, and show that natural groupings are formed.} }

@article{
  orchid34,
  month = {November},
  title = {Statistics of Stellar Variability from Kepler - I: Revisiting Quarter 1 with an Astrophysically Robust Systematics Correction. },
  author = {S McQuillan and S Aigrain and Stephen J Roberts},
  year = {2011},
  journal = {Astronomy and Astrophysics},
  keywords = {Machine Learning, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/34/1/1111.5580v2.pdf} }

@article{
  orchid21,
  month = {October},
  title = {On the Existence of Pure Strategy Nash Equilibria in Integer-Splittable Weighted Congestion Games},
  author = {Long Tran-Thanh and Maria Polukarov and Archie C Chapman and Alex Rogers and Nicholas R Jennings},
  year = {2011},
  pages = {236--253},
  journal = {Proc. of 4th International Symposium on Algorithmic Game Theory (SAGT),},
  keywords = {Mechanism Design, Incentive Engineering},
  howpublished = {http://www.orchid.ac.uk/eprints/21/1/SAGT2011cmrd.pdf},
abstract = {We study the existence of pure strategy Nash equilibria (PSNE) in integer?splittable weighted congestion games (ISWCGs), where agents can strategically assign different amounts of demand to different resources, but must distribute this demand in fixed-size parts. Such scenarios arise in a wide range of application domains, including job scheduling and network routing, where agents have to allocate multiple tasks and can assign a number of tasks to a particular selected resource. Specifically, in an ISWCG, an agent has a certain total demand (aka weight) that it needs to satisfy, and can do so by requesting one or more integer units of each resource from an element of a given collection of feasible subsets.1 Each resource is associated with a unit?cost function of its level of congestion; as such, the cost to an agent for using a particular resource is the product of the resource unit?cost and the number of units the agent requests. While general ISWCGs do not admit PSNE (Rosenthal, 1973b), the restricted subclass of these games with linear unit?cost functions has been shown to possess a potential function (Meyers, 2006), and hence, PSNE. However, the linearity of costs may not be necessary for the existence of equilibria in pure strategies. Thus, in this paper we prove that PSNE always exist for a larger class of convex and monotonically increasing unit?costs. On the other hand, our result is accompanied by a limiting asumption on the structure of agents? strategy sets: specifically, each agent is associated with its set of accessible resources, and can distribute its demand across any subset of these resources. Importantly, we show that neither monotonicity nor convexity on its own guarantees this result. Moreover, we give a counterexample with monotone and semi?convex cost functions, thus distinguishing ISWCGs from the class of infinitely?splittable congestion games for which the conditions of monotonicity and semi?convexity have been shown to be sufficient for PSNE existence (Rosen, 1965). Furthermore, we demonstrate that the finite improvement path property (FIP) does not hold for convex increasing ISWCGs. Thus, in contrast to the case with linear costs, a potential function argument cannot be used to prove our result. Instead, we provide a procedure that converges to an equilibrium from an arbitrary initial strategy profile, and in doing so show that ISWCGs with convex increasing unit?cost functions are weakly acyclic.} }

@article{
  orchid20,
  volume = {175},
  number = {14},
  month = {September},
  author = {Sebastian Stein and Enrico H Gerding and Alex Rogers and Kate Larson and Nicholas R Jennings},
  title = {Algorithms and mechanisms for procuring services with uncertain durations using redundancy },
  publisher = {Elsevier},
  year = {2011},
  journal = {Artificial Intelligence},
  pages = {2021--2060},
  keywords = {Mechanism Design, Applications, Incentive Engineering},
  howpublished = {http://www.orchid.ac.uk/eprints/20/1/SteinAIJ.pdf},
abstract = {In emerging service-oriented systems, such as computational clouds or grids, software agents are able to automatically procure distributed services to complete computational tasks. However, service execution times are often highly uncertain and service providers may have incentives to lie strategically about this uncertainty to win more customers. In this paper, we argue that techniques from the field of artificial intelligence are instrumental to addressing these challenges. To this end, we first propose a new decision-theoretic algorithm that allows a single service consumer agent to procure services for a computational task with a strict deadline. Crucially, this algorithm uses redundancy in a principled manner to mitigate uncertain execution times and maximise the consumer[modifier letter apostrophe]s expected utility. We present both an optimal variant that uses a novel branch-and-bound formulation, and a fast heuristic that achieves near-optimal performance. Using simulations, we demonstrate that our algorithms outperform approaches that do not employ redundancy by up to 130% in some settings. Next, as the algorithms require private information about the providers[modifier letter apostrophe] capabilities, we show how techniques from mechanism design can be used to incentivise truthfulness. As no existing work in this area deals with uncertain execution times and redundant invocations, we extend the state of the art by proposing a number of payment schemes for these settings. In a detailed analysis, we prove that our mechanisms fulfil a range of desirable economic properties, including incentive compatibility, and we discuss suboptimal variants that scale to realistic settings with hundreds of providers. We show experimentally that our mechanisms extract a high surplus and that even our suboptimal variants typically achieve a high efficiency (95% or more in a wide range of settings).} }

@techreport{
  orchid126,
  month = {February},
  author = {Nicholas R Jennings and Stephen J Roberts and T Rodden and Luc Moreau and Alex Rogers and Sarvapali D Ramchurn and David Nicholson},
  address = {Southampton},
  title = {ORCHID End of Year Report 2011},
  type = {Project Report},
  publisher = {University of Southampton},
  institution = {University of Southampton},
  year = {2011},
  keywords = {Accountable Information Infrastructure, Applications, Agile Teaming, Flexible Autonomy, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/126/1/End%20of%20Year%20Report%202011.pdf} }

@article{
  orchid33,
  title = {A GPU-based survey for millisecond radio transients using ARTEMIS.},
  author = {W Armour and A Karastergiou and M Giles and C Williams and K Magro and S Zagkouris and Stephen J Roberts and S Salvini and F Dulwich and B Mort},
  publisher = {ADASS},
  year = {2011},
  journal = {Proc. of ADASS XXI},
  keywords = {Machine Learning, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/33/1/1111.6399v1.pdf} }

@techreport{
  orchid36,
  number = {PARG-11-01},
  author = {Jan-P Calliess and D Lyons and U.D. Hanebeck},
  address = {Oxford},
  title = {Lazy auctions for multi-robot collision avoidance and motion control under uncertainty.},
  type = {Technical Report},
  publisher = {University of Oxford},
  year = {2011},
  institution = {University of Oxford},
  journal = {ACM Transactions of Sensor Networks},
  keywords = {Machine Learning, Agile Teaming, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/36/1/PARG%5f01%5f11.pdf} }

@article{
  orchid31,
  title = {Cooperatives of Distributed Energy Resources for Efficient Virtual Power Plants},
  author = {G Chalkiadakis and Valentin Robu and R Kota and Alex Rogers and Nicholas R Jennings},
  publisher = {AAMAS},
  year = {2011},
  pages = {787--794},
  journal = {Proc. Tenth Int. Conference on Autonomous Agents and Multiagent Systems},
  keywords = {Decentralised Control, Applications, Agile Teaming, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/31/1/ccrjVPPcoop.pdf} }

@article{
  orchid76,
  volume = {9},
  number = {2},
  title = {Graph marginalization for rapid assignment in wide-area surveillance},
  author = {Mark Ebden and Stephen Roberts},
  year = {2011},
  pages = {180--188},
  journal = {Ad Hoc Networks},
  keywords = {Decentralised Control, Mechanism Design, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/76/1/AdHocNetworks.pdf} }

@article{
  orchid40,
  title = {A tutorial on variational Bayesian inference},
  author = {Charles W. Fox and Stephen J. Roberts},
  year = {2011},
  journal = {Artificial Intelligence Review},
  keywords = {Machine Learning, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/40/1/fox%5fvbtut.pdf} }

@article{
  orchid14,
  title = {Online Mechanism Design for Electric Vehicle Charging},
  author = {Enrico H Gerding and Valentin Robu and Sebastian Stein and David Parkes and Alex Rogers and Nicholas R Jennings},
  year = {2011},
  journal = {Proc. of The Tenth International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS 2011)},
  keywords = {Mechanism Design, Applications, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/14/1/AAMAS440%5fcameraready.pdf} }

@article{
  orchid35,
  title = {A Gaussian process framework for modelling instrumental systematics: application to transmission spectroscopy. },
  author = {N.P. Gibson and S Aigrain and Stephen J Roberts and T.M. Evans and Michael A Osborne and F Pont},
  year = {2011},
  journal = {Monthly Notices of the Royal Astronomical Society},
  keywords = {Machine Learning, Incentive Engineering},
  howpublished = {http://www.orchid.ac.uk/eprints/35/1/1109.3251v2.pdf},
abstract = {Transmission spectroscopy, which consists of measuring the wavelength-dependent absorption of starlight by a planet's atmosphere during a transit, is a powerful probe of atmospheric composition. However, the expected signal is typically orders of magnitude smaller than instrumental systematics, and the results are crucially dependent on the treatment of the latter. In this paper, we propose a new method to infer transit parameters in the presence of systematic noise using Gaussian processes, a technique widely used in the machine learning community for Bayesian regression and classification problems. Our method makes use of auxiliary information about the state of the instrument, but does so in a non-parametric manner, without imposing a specific dependence of the systematics on the instrumental parameters, and naturally allows for the correlated nature of the noise. We give an example application of the method to archival NICMOS transmission spectroscopy of the hot Jupiter HD 189733, which goes some way towards reconciling the controversy surrounding this dataset in the literature. Finally, we provide an appendix giving a general introduction to Gaussian processes for regression, in order to encourage their application to a wider range of problems. } }

@article{
  orchid41,
  volume = {415},
  number = {1},
  title = {A transient component in the pulse profile of PSR J0738?4042},
  author = {A. Karastergiou and S. J. Roberts and S. Johnston and H. Lee and P. Weltevrede and M. Kramer},
  year = {2011},
  pages = {251--256},
  journal = {Monthly Notices of the Royal Astronomical Society},
  keywords = {Machine Learning, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/41/1/1103.2247v1.pdf} }

@article{
  orchid37,
  title = {Chance-constrained Model Predictive Control for Multi-Agent Systems.},
  author = {D Lyons and Jan-P Calliess and U.D. Hanebeck},
  publisher = {arXiv},
  year = {2011},
  journal = {arXiv},
  keywords = {Agent-based Computing, Incentive Engineering},
  howpublished = {http://www.orchid.ac.uk/eprints/37/1/1104.5384v3.pdf},
abstract = {We consider stochastic model predictive control of a multi-agent systems with constraints on the probabilities of inter-agent collisions. We first study a sample-based approximation of the collision probabilities and use this approximation to formulate constraints for the stochastic control problem. This approximation will converge as the number of samples goes to infinity, however, the complexity of the resulting control problem is so high that this approach proves unsuitable for control under real-time requirements. To alleviate the computational burden we propose a second approach that uses probabilistic bounds to determine regions with increased probability of presence for each agent and formulate constraints for the control problem that guarantee that these regions will not overlap. We prove that the resulting problem is conservative for the original problem with probabilistic constraints, ie. every control strategy that is feasible under our new constraints will automatically be feasible for the original problem. Furthermore we show in simulations in a UAV path planning scenario that our proposed approach grants significantly better run-time performance compared to a controller with the sample-based approximation with only a small degree of sub-optimality resulting from the conservativeness of our new approach. } }

@article{
  orchid16,
  volume = {175},
  number = {2},
  title = {Mechanism Design for the Truthful Elicitation of Costly Probabilistic Estimates in Distributed Information Systems},
  author = {Athanasios Papakonstantinou and Alex Rogers and Enrico H Gerding and Nicholas R Jennings},
  year = {2011},
  pages = {648--672},
  journal = {Artificial Intelligence},
  keywords = {Mechanism Design, Incentive Engineering},
  howpublished = {http://www.orchid.ac.uk/eprints/16/1/4120.pdf},
  abstract = {This paper reports on the design of a novel two-stage mechanism, based on {$backslash$}textit{strictly proper scoring rules},
that allows a centre to acquire a costly forecast of a future event (such as a meteorological phenomenon or a probabilistic estimate of a specific parameter such as the quality of an expected service), with a specified minimum precision, from one or more agents. In particular, this is the first mechanism that can be applied in a setting where the centre has no knowledge about the actual costs involved in the generation of the agents' estimates and {$backslash$}textit{also} has no means of evaluating the quality and accuracy of the estimates it receives. En route to this mechanism, we first consider a setting in which any single agent can provide an estimate of the required precision, and the centre can evaluate this estimate by comparing it with the outcome which is observed at a later stage. This mechanism is then extended, so that it can be applied in a setting where the agents' different capabilities are reflected in the maximum precision of the estimates that they can provide, and hence the centre may need to select multiple agents and combine their individual results in order to obtain an estimate of the required precision. For all three mechanisms, we prove their economic properties (i.e. incentive compatibility and individual rationality) and then present specific empirical results. For the single agent mechanism we compare the quadratic, spherical and logarithmic scoring rules with a parametric family of scoring rules. We show that although the logarithmic scoring rule minimises both the mean and variance of the centre's total payments, using this rule means that an agent may face an unbounded penalty if it provides an estimate of extremely poor quality. We show that this is not the case for the parametric family, and thus, we suggest that the parametric scoring rule is the best candidate in our setting. Furthermore, we show that the `multiple agent' extension describes a family of possible approaches to select agents in the first stage of our mechanism, and we show empirically and prove analytically that there is one approach that dominates all others. Finally, we compare our novel contribution and with the peer prediction mechanism introduced by {$backslash$}cite{trustsr1} and show that the centre's total expected payment is the same in both mechanisms (and is equal to total expected payment in the case that the estimates can be compared to the actual outcome), while the variance in these payments is significantly reduced within our mechanism.} }

@article{
  orchid38,
  volume = {83},
  number = {6},
  title = {Overlapping Community Detection using Bayesian Nonnegative Matrix Factorization.},
  author = {Ioannis Psorakis and Stephen J Roberts and Mark Ebden and Ben Sheldon},
  year = {2011},
  journal = {Physical Review E},
  keywords = {Machine Learning, Incentive Engineering},
  howpublished = {http://www.orchid.ac.uk/eprints/38/1/PRE%5fNMF.pdf},
abstract = {Identifying overlapping communities in networks is a challenging task. In this work we present a probabilistic approach to community detection that utilizes a Bayesian non-negative matrix factorization model to extract overlapping modules from a network. The scheme has the advantage of soft-partitioning solutions, assignment of node participation scores to modules, and an intuitive foundation. We present the performance of the method against a variety of benchmark problems and compare and contrast it to several other algorithms for community detection.} }

@article{
  orchid39,
  title = {Determining intent using hard/soft data and Gaussian process classifiers.},
  author = {Steven Reece and Stephen J Roberts and David Nicholson and C Lloyd},
  year = {2011},
  journal = {Proc. of the 14th International Conference on Information Fusion 2011},
  keywords = {Machine Learning, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/39/1/gp%5frvm%5ffusion%5f2011.pdf} }

@inproceedings{
  orchid75,
  booktitle = {NIPS 2011},
  title = {Variational Bayesian Learning of Sparse Representations and its Application in Functional Neuroimaging.},
  author = {E Roussos and Stephen J Roberts and I Daubechies},
  year = {2011},
  keywords = {Machine Learning, Incentive Engineering},
howpublished = {http://www.orchid.ac.uk/eprints/75/1/MLINI-2011%5ftext%5ffinal.pdf} }