Publications


2017/2018


 WG1


[1] E. Anshelevich, O. Bhardwaj, and M. Hoefer, Stable matching with network externalities, Al- gorithmica, 78 (2017), pp. 1067–1106.
[2] Y. Azar, M. Hoefer, I. Maor, R. Reiffenha ̈user, and B. Vo ̈cking, Truthful mechanism design via correlated tree rounding, Math. Program., 163 (2017), pp. 445–469.
[3] H. Aziz, P. Goldberg, and T. Walsh, Equilibria in sequential allocation, in Algorithmic Decision Theory – 5th International Conference, ADT 2017, Luxembourg, Luxembourg, October 25-27, 2017, Proceedings, 2017, pp. 270–283.
[4] X. Bei, J. Garg, M. Hoefer, and K. Mehlhorn, Earning limits in fisher markets with spending- constraint utilities, in Bil`o and Flammini [6], pp. 67–79.
[5] D. Bilo` and P. Lenzner, On the tree conjecture for the network creation game, in 35th Symposium on Theoretical Aspects of Computer Science, STACS 2018, February 28 to March 3, 2018, Caen, France, 2018, pp. 14:1–14:15.
[6] V. Bilo` and M. Flammini, eds., Algorithmic Game Theory – 10th International Symposium, SAGT 2017, L’Aquila, Italy, September 12-14, 2017, Proceedings, vol. 10504 of Lecture Notes in Computer Science, Springer, 2017.
[7] V. Bilo`, L. Moscardelli, and C. Vinci, Uniform mixed equilibria in network congestion games with link failures, in Chatzigiannakis et al. [11], pp. 146:1–146:14.
[8] V. Bilo` and C. Vinci, On the impact of singleton strategies in congestion games, in 25th Annual European Symposium on Algorithms, ESA 2017, September 4-6, 2017, Vienna, Austria, 2017, pp. 17:1– 17:14.
[9] A. Bjelde, M. Klimm, and D. Schmand, Brief announcement: Approximation algorithms for un- splittable resource allocation problems with diseconomies of scale, in Proceedings of the 29th ACM Symposium on Parallelism in Algorithms and Architectures, SPAA 2017, Washington DC, USA, July 24-26, 2017, C. Scheideler and M. T. Hajiaghayi, eds., ACM, 2017, pp. 227–229.
[10] I. Caragiannis, V. Gkatzelis, and C. Vinci, Coordination mechanisms, cost-sharing, and approx- imation algorithms for scheduling, in Devanur and Lu [28], pp. 74–87.
[11] I. Chatzigiannakis, C. Kaklamanis, D. Marx, and D. Sannella, eds., 45th International Col- loquium on Automata, Languages, and Programming, ICALP 2018, July 9-13, 2018, Prague, Czech Republic, vol. 107 of LIPIcs, Schloss Dagstuhl – Leibniz-Zentrum fuer Informatik, 2018.
[12] A. Chauhan, P. Lenzner, A. Melnichenko, and L. Molitor, Selfish network creation with non- uniform edge cost, in Bil`o and Flammini [6], pp. 160–172.
[13] A. Chauhan, P. Lenzner, and L. Molitor, Schelling segregation with strategic agents, in Algo- rithmic Game Theory – 11th International Symposium, SAGT 2018, Beijing, China, September 11-14, 2018, Proceedings, 2018, pp. 137–149.
[14] G. Christodoulou, M. Gairing, Y. Giannakopoulos, and P. G. Spirakis, The price of stability of weighted congestion games, in Chatzigiannakis et al. [11], pp. 150:1–150:16.
[15] G. Christodoulou, M. Gairing, S. E. Nikoletseas, C. Raptopoulos, and P. G. Spirakis, A 3-player protocol preventing persistence in strategic contention with limited feedback, in Bil`o and Flammini [6], pp. 240–251.
[16] R. Colini-Baldeschi, R. Cominetti, P. Mertikopoulos, and M. Scarsini, The asymptotic behavior of the price of anarchy, in Devanur and Lu [28], pp. 133–145.
[17] R. Colini-Baldeschi, P. W. Goldberg, B. de Keijzer, S. Leonardi, T. Roughgarden, and S. Turchetta, Approximately efficient two-sided combinatorial auctions, in Proceedings of the 2017 ACM Conference on Economics and Computation, EC ’17, Cambridge, MA, USA, June 26-30, 2017, 2017, pp. 591–608.
[18] R. Colini-Baldeschi, M. Klimm, and M. Scarsini, Demand-independent optimal tolls, in Chatzi- giannakis et al. [11], pp. 151:1–151:14.
[19] R. Cominetti, T. Harks, C. Osorio, and B. Peis, Dynamic traffic models in transportation science (dagstuhl seminar 18102), Dagstuhl Reports, 8 (2018), pp. 21–38.
[20] J. Correa, C. Guzma ́n, T. Lianeas, E. Nikolova, and M. Schro ̈der, Network pricing: How to induce optimal flows under strategic link operators, in Proceedings of the 2018 ACM Conference on Economics and Computation, Ithaca, NY, USA, June 18-22, 2018, 2018, pp. 375–392.
[21] J. Correa, R. Hoeksma, and M. Schro ̈der, Network congestion games are robust to variable demand, in International Conference on Web and Internet Economics, Springer, 2017, p. 397.
[22] J. R. Correa, T. Harks, V. J. C. Kreuzen, and J. Matuschke, Fare evasion in transit networks, Operations Research, 65 (2017), pp. 165–183.
[23] D. Crapis, B. Ifrach, C. Maglaras, and M. Scarsini, Monopoly pricing in the presence of social learning, Management Science, 63 (2017).
[24] J. de Jong, W. Kern, B. Steenhuisen, and M. Uetz, The asymptotic price of anarchy for k- uniform congestion games, in Solis-Oba and Fleischer [74], pp. 317–328.
[25] A. Deligkas, J. Fearnley, and R. Savani, Computing constrained approximate equilibria in poly- matrix games, in Algorithmic Game Theory – 10th International Symposium, SAGT 2017, L’Aquila, Italy, September 12-14, 2017, Proceedings, 2017, pp. 93–105.
[26] A. Deligkas, J. Fearnley, R. Savani, and P. G. Spirakis, Computing approximate nash equilibria in polymatrix games, Algorithmica, 77 (2017), pp. 487–514.
[27] X. Deng, P. W. Goldberg, Y. Sun, B. Tang, and J. Zhang, Pricing ad slots with consecutive multi-unit demand, Autonomous Agents and Multi-Agent Systems, 31 (2017), pp. 584–605.
[28] N. R. Devanur and P. Lu, eds., Web and Internet Economics – 13th International Conference, WINE 2017, Bangalore, India, December 17-20, 2017, Proceedings, vol. 10660 of Lecture Notes in Computer Science, Springer, 2017.
[29] P. Du ̈tting, M. Feldman, T. Kesselheim, and B. Lucier, Prophet inequalities made easy: Stochastic optimization by pricing non-stochastic inputs, in Proceedings of the 58th IEEE Annual Sym- posium on Foundations of Computer Science, FOCS 2017, Berkeley, CA, USA, October 2017, 2017, pp. 540–551.[30] P. Du ̈tting, F. A. Fischer, and D. C. Parkes, Expressiveness and robustness of first-price position auctions, Mathematics of Operations Research, (Forthcoming).
[31] P. Du ̈tting, V. Gkatzelis, and T. Roughgarden, The performance of deferred-acceptance auc- tions, Mathematics of Operations Research, 42 (2017).
[32] P. Du ̈tting, M. Henzinger, and M. Starnberger, Valuation compressions in vcg-based combina- torial auctions, ACM Trans. Econ. Comput., 6 (2018), pp. 5:1–5:18.
[33] P. Du ̈tting and T. Kesselheim, Best-response dynamics in combinatorial auctions with item bidding, in Proceedings of the Twenty-Eighth Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2017, Barcelona, Spain, January 2017, 2017, pp. 521–533.
[34] P. Du ̈tting, I. Talgam-Cohen, and T. Roughgarden, Modularity and greed in double auctions, Games and Economic Behavior, 105 (2017), pp. 59–83.
[35] F. Eisenbrand and J. Ko ̈nemann, eds., Integer Programming and Combinatorial Optimization – 19th International Conference, IPCO 2017, Waterloo, ON, Canada, June 26-28, 2017, Proceedings, vol. 10328 of Lecture Notes in Computer Science, Springer, 2017.
[36] M. Epitropou, D. Fotakis, M. Hoefer, and S. Skoulakis, Opinion formation games with aggre- gation and negative influence, in Bil`o and Flammini [6], pp. 173–185.
[37] M. Etscheid and H. Ro ̈glin, Smoothed analysis of local search for the maximum-cut problem, ACM Trans. Algorithms, 13 (2017), pp. 25:1–25:12.
[38] J. Fearnley, M. Gairing, M. Mnich, and R. Savani, Reachability switching games, in Chatzigian- nakis et al. [11], pp. 124:1–124:14.
[39] M. Feldman, Y. Snappir, and T. Tamir, The efficiency of best-response dynamics, in The 10th International Symposium on Algorithmic Game Theory (SAGT), 2017, pp. 186–198.
[40] M. Feldotto, M. Gairing, G. Kotsialou, and A. Skopalik, Computing approximate pure nash equilibria in shapley value weighted congestion games, in Devanur and Lu [28], pp. 191–204.
[41] A. Filos-Ratsikas and P. W. Goldberg, Consensus halving is ppa-complete, in Proceedings of the 50th Annual ACM SIGACT Symposium on Theory of Computing, STOC 2018, Los Angeles, CA, USA, June 25-29, 2018, 2018, pp. 51–64.
[42] D. Fotakis, A. Pagourtzis, and V. T. Paschos, eds., Algorithms and Complexity – 10th Interna- tional Conference, CIAC 2017, Athens, Greece, May 24-26, 2017, Proceedings, vol. 10236 of Lecture Notes in Computer Science, 2017.
[43] T. Friedrich, S. Ihde, C. Keßler, P. Lenzner, S. Neubert, and D. Schumann, Brief an- nouncement: Efficient best response computation for strategic network formation under attack, in Pro- ceedings of the 29th ACM Symposium on Parallelism in Algorithms and Architectures, SPAA 2017, Washington DC, USA, July 24-26, 2017, 2017, pp. 321–323.
[44] , Efficient best response computation for strategic network formation under attack, in Bil`o and Flammini [6], pp. 199–211.
[45] S. Fujishige, M. X. Goemans, T. Harks, B. Peis, and R. Zenklusen, Matroids are immune to braess’ paradox, Math. Oper. Res., 42 (2017), pp. 745–761.
[46] M. Gairing, T. Harks, and M. Klimm, Complexity and approximation of the continuous network design problem, SIAM Journal on Optimization, 27 (2017), pp. 1554–1582.
[47] M. Gairing, K. Kollias, and G. Kotsialou, Cost-sharing in generalised selfish routing, in Fotakis et al. [42], pp. 272–284.
[48] J. Garg, M. Hoefer, and K. Mehlhorn, Approximating the nash social welfare with budget-additive valuations, in Proceedings of the Twenty-Ninth Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2018, New Orleans, LA, USA, January 7-10, 2018, 2018, pp. 2326–2340.
[49] P. W. Goldberg, Y. Mansour, and P. Du ̈tting, Game theory meets computational learning theory (dagstuhl seminar 17251), Dagstuhl Reports, 7 (2017), pp. 68–85.
[50] P. W. Goldberg and S. Turchetta, Query complexity of approximate equilibria in anonymous games, J. Comput. Syst. Sci., 90 (2017), pp. 80–98.
[51] C. Gottschalk, A. M. C. A. Koster, F. Liers, B. Peis, D. Schmand, and A. Wierz, Robust flows over time: models and complexity results, Math. Program., 171 (2018), pp. 55–85.
[52] V. Gupta, B. Moseley, M. Uetz, and Q. Xie, Stochastic online scheduling on unrelated machines, in Eisenbrand and Ko ̈nemann [35], pp. 228–240.
[53] T. Harks, M. Hoefer, A. Huber, and M. Surek, Efficient black-box reductions for separable cost sharing, in Chatzigiannakis et al. [11], pp. 154:1–154:15.
[54] T. Harks, A. Huber, and M. Surek, A characterization of undirected graphs admitting optimal cost shares, in Devanur and Lu [28], pp. 237–251.
[55] T. Harks, M. Klimm, and B. Peis, Sensitivity analysis for convex separable optimization over integral polymatroids, SIAM Journal on Optimization, 28 (2018), pp. 2222–2245.
[56] T. Harks, M. Klimm, and M. Schneider, Bottleneck routing with elastic demands, Oper. Res. Lett., 46 (2018), pp. 93–98.
[57] T. Harks, B. Peis, D. Schmand, B. Tauer, and L. V. Koch, Competitive packet routing with priority lists, ACM Trans. Economics and Comput., 6 (2018), pp. 4:1–4:26.
[58] T. Harks, M. Schro ̈der, and D. Vermeulen, Toll caps in privatized road networks, CoRR, abs/1802.10514 (2018).
[59] T. Harks and V. Timmermans, Equilibrium computation in atomic splittable singleton congestion games, in Eisenbrand and K ̈onemann [35], pp. 442–454.
[60] , Computing equilibria in atomic splittable polymatroid congestion games with convex costs, CoRR, abs/1808.04712 (2018).
[61] , Uniqueness of equilibria in atomic splittable polymatroid congestion games, J. Comb. Optim., 36 (2018), pp. 812–830.
[62] M. Hoefer and W. Jiamjitrak, On proportional allocation in hedonic games, in Bil`o and Flammini [6], pp. 307–319.
[63] M. Hoefer and B. Kodric, Combinatorial secretary problems with ordinal information, in 44th International Colloquium on Automata, Languages, and Programming, ICALP 2017, July 10-14, 2017, Warsaw, Poland, 2017, pp. 133:1–133:14.
[64] M. Hoefer, D. Vaz, and L. Wagner, Dynamics in matching and coalition formation games with structural constraints, Artif. Intell., 262 (2018), pp. 222–247.
[65] M. Hoefer and L. Wagner, Locally stable marriage with strict preferences, SIAM J. Discrete Math., 31 (2017), pp. 283–316.
[66] E. Iwanir and T. Tamir, Analysis and Experimental Study of Heuristics for Job Scheduling Reopti- mization Problems, Springer International Publishing, 2018, pp. 207–233.
[67] O. Kupferman and T. Tamir, Hierarchical network formation games, in The 23rd International Conference on Tools and Algorithms for the Construction and Analysis of Systems (TACAS), 2017, pp. 229–246.
[68] J. Matuschke, S. T. McCormick, G. Oriolo, B. Peis, and M. Skutella, Protection of flows under targeted attacks, Oper. Res. Lett., 45 (2017), pp. 53–59.
[69] A. Mu ̈ller, M. Scarsini, I. Tsetlin, and R. L. Winkler, Between first- and second-order stochas- tic dominance, Management Science, 63 (2017), pp. 2933–2947.
[70] B. Peis, B. Tauer, V. Timmermans, and L. V. Koch, Oligopolistic competitive packet routing, in 18th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems, ATMOS 2018, August 23-24, 2018, Helsinki, Finland, 2018, pp. 13:1–13:22.
[71] H. Peters, M. Schro ̈der, and D. Vermeulen, Hotelling’s location model with negative network externalities, International Journal of Game Theory, (2018), pp. 1–27.
[72] M. Scarsini, M. Schro ̈der, and T. Tomala, Dynamic atomic congestion games with seasonal flows, Operations Research, 66 (2018), pp. 327–339.
[73] B. Schieber, H. Shachnai, G. Tamir, and T. Tamir, A theory and algorithms for combinatorial reoptimization, Algorithmica, 80 (2017).
[74] R. Solis-Oba and R. Fleischer, eds., Approximation and Online Algorithms – 15th International Workshop, WAOA 2017, Vienna, Austria, September 7-8, 2017, Revised Selected Papers, vol. 10787 of Lecture Notes in Computer Science, Springer, 2018.
[75] T. Tamir, The power of one secret agent, in Proceedings of the 10th International Conference on Fun with Algorithms, FUN’18, 2018.
[76] K. Tuyls, J. Perolat, M. Lanctot, G. Ostrovski, R. Savani, J. Leibo, T. Ord, T. Graepel, and S. Legg, Symmetric decomposition of asymmetric games, Scientific Reports, 8 (2018), p. Article number: 1015 (20 pages).


WG2


[1] E. V. Belmega, P. Mertikopoulos, R. Negrel, and L. Sanguinetti, Online convex optimization and no-regret learning: Algorithms, guarantees and applications. https://arxiv.org/abs/1804.04529, 2018.
[2] O. Besbes and M. Scarsini, On information distortions in online ratings, Oper. Res., 66 (2018), pp. 597–610.
[3] M. Bravo, D. S. Leslie, and P. Mertikopoulos, Bandit learning in concave N-person games, in NIPS ’18: Proceedings of the 32nd International Conference on Neural Information Processing Systems, 2018.
[4] N. Cesa-Bianchi, T. Cesari, and V. Perchet, Dynamic pricing with finitely many unknown valu- ations, CoRR, abs/1807.03288 (2018).
[5] N. Cesa-Bianchi, C. Gentile, and Y. Mansour, Delay and cooperation in nonstochastic bandits. Submitted for journal publication.
[6] , Nonstochastic bandits with composite anonymous feedback, in Conference On Learning Theory, COLT 2018, Stockholm, Sweden, 6-9 July 2018., 2018, pp. 750–773.
[7] N. Cesa-Bianchi and O. Shamir, Bandit regret scaling with the effective loss range, in Algorithmic Learning Theory, ALT 2018, 7-9 April 2018, Lanzarote, Canary Islands, Spain, 2018, pp. 128–151.
[8] R. Colini-Baldeschi, R. Cominetti, P. Mertikopoulos, and M. Scarsini, The asymptotic behavior of the price of anarchy, in Web and Internet Economics: 13th International Conference, WINE 2017, N. R. Devanur and P. Lu, eds., Cham, 2017, Springer International Publishing, pp. 133–145.
[9] R. Colini-Baldeschi, R. Cominetti, P. Mertikopoulos, and M. Scarsini, When is selfish routing bad? The price of anarchy in light and heavy traffic. https://arxiv.org/abs/1703.00927, 2018.
[10] R. Colini-Baldeschi, M. Klimm, and M. Scarsini, Demand-independent optimal tolls, in 45th International Colloquium on Automata, Languages, and Programming (ICALP 2018), I. Chatzigian- nakis, C. Kaklamanis, D. Marx, and D. Sannella, eds., Dagstuhl, Germany, 2018, Leibniz-Zentrum fu ̈r Informatik, pp. 151:1–151:14.
[11] R. Colini-Baldeschi, M. Scarsini, and S. Vaccari, Variance allocation and Shapley value, Methodol. Comput. Appl. Probab., 20 (2018), pp. 919–933.
[12] D. Crapis, B. Ifrach, C. Maglaras, and M. Scarsini, Monopoly pricing in the presence of social learning, Management Sci., 63 (2017), pp. 3586–3608.
[13] B. Duvocelle, P. Mertikopoulos, M. Staudigl, and D. Vermeulen, Learning in time-varying games. https://arxiv.org/abs/1809.03066, 2018.
[14] M. Leconte, G. Paschos, P. Mertikopoulos, and U. Kozat, A resource allocation framework for network slicing, in INFOCOM ’18: Proceedings of the 37th IEEE International Conference on Computer Communications, 2018.
[15] P. Mertikopoulos, C. H. Papadimitriou, and G. Piliouras, Cycles in adversarial regularized learning, in SODA ’18: Proceedings of the 29th annual ACM-SIAM Symposium on Discrete Algorithms, 2018.
[16] P. Mertikopoulos and W. H. Sandholm, Riemannian game dynamics, Journal of Economic Theory, 177 (2018), pp. 315–364.
[17] P. Mertikopoulos and M. Staudigl, Stochastic mirror descent dynamics and their convergence in monotone variational inequalities, Journal of Optimization Theory and Applications, (2018).
[18] P. Mertikopoulos, H. Zenati, B. Lecouat, C.-S. Foo, V. Chandrasekhar, and G. Piliouras, Mirror descent in saddle-point problems: Going the extra (gradient) mile. https://arxiv.org/abs/ 1807.02629, 2018.
[19] P. Mertikopoulos and Z. Zhou, Learning in games with continuous action sets and unknown payoff functions, Mathematical Programming, (2018).
[20] A. Mu ̈ller, M. Scarsini, I. Tsetlin, and R. L. Winkler, Between first and second-order stochastic dominance, Management Sci., 63 (2017), pp. 2933–2947.
[21] M. Nu ́n ̃ez and M. Scarsini, Large spatial competition, in Spatial Interaction Models : Facility Lo- cation Using Game Theory, L. Mallozzi, E. D’Amato, and P. M. Pardalos, eds., Springer International Publishing, 2017, pp. 225–246.
[22] M. Scarsini, M. Schro ̈der, and T. Tomala, Dynamic atomic congestion games with seasonal flows, Oper. Res., 66 (2018), pp. 327–339.
[23] L. Vigneri, P. Mertikopoulos, and G. Paschos, Large-scale network utility maximization: Coun- tering exponential growth with exponentiated gradients. submitted, 2018.
[24] A. Ward, D. Miller, Z. Zhou, P. Mertikopoulos, and N. Bambos, Power control with random delays: Robust feedback averaging, in CDC ’18: Proceedings of the 56th IEEE Annual Conference on Decision and Control, 2018.
[25] Z. Zhou, P. Mertikopoulos, S. Athey, N. Bambos, P. W. Glynn, and Y. Ye, Multi-agent online learning with asynchronous feedback loss, in NIPS ’18: Proceedings of the 32nd International Conference on Neural Information Processing Systems, 2018.
[26] Z. Zhou, P. Mertikopoulos, N. Bambos, P. W. Glynn, Y. Ye, J. Li, and F.-F. Li, Distributed asynchronous optimization with unbounded delays: How slow can you go?, in ICML ’18: Proceedings of the 35th International Conference on Machine Learning, 2018.
[28] Thiparat Chotibut, Fryderyk Falniowski, Michal Misiurewicz, Georgios Piliouras, “Family of chaotic maps from game theory”, submitted. Arxived at https://arxiv.org/pdf/1807.06831.pdf
[29] K. Soric, M. Zekic-Susac, “Is operational research attractive enough at Croatian universities?” Scientific book “Advances in Operations Research Education – European Studies”, by Springer Verlag (https://www.springer.com/la/book/9783319741031), 2017.
[30] J. Kraljević, K. Šorić, V. Vojvodić Rosenzweig, Price changing and inventory sharing in supply chain management, Croatian Operational Research Review, Vol. 8., str. 181.-192., 2017., https://hrcak.srce.hr/181656?lang=en
[31] Y. Heller and E. Mohlin, “Social Learning and the Shadow of the Past”, Journal of Economic Theory,  177, 426-460, 2018.  Available online: https://www.sciencedirect.com/science/article/pii/S0022053118303533

[32] Immanuel M. Bomze and Mertikopoulos, Panayotis and Staudigl, Mathias and Schachinger, Werner, A Hessian-Riemannian Barrier Method for linearly constrained optimization,  Arxived at https://arxiv.org/abs/1809.09449
[33] Y. Heller and E. Mohlin, “Observations on cooperation”, Review of Economic Studies, forthcoming.
Available online: http://www.restud.com/paper/observations-on-cooperation/

[34] P. Mertikopolous, M. Staudigl, Convergence to Nash equilibrium in continuous games with noisy first-order feedback, 56th IEEE Conference on Decision and Control 2017

[35] Lazy fully probabailistic Design: Application potential. T.V.Guy, S.Fakhimi, J.Stech. Published in: Multi-Agent Systems and Agreement Technologies, LNAI
Eds: Belardinelli F. and Argente S., Springer 2018

[36] On Decentralized Implicit Negotiation in Modified Ultimatum Game. J.Homolova, E.Zugarova, M.Karny,T.V.Guy Published in: Multi-Agent Systems and Agreement Technologies, LNAI Eds: Belardinelli F. and Argente S., Springer 2018
Status: accepted/published www.springer.com/us/book/9783030017125


WG3


[1] Paul Hunter, Arno Pauly, Guillermo A. Pérez, Jean-François Raskin: Mean-payoff games with partial observation. Theor. Comput. Sci. 735: 82-110 (2018).

[2] Jan Kretínský, Guillermo A. Pérez, Jean-François Raskin: Learning-Based Mean-Payoff Optimization in an Unknown MDP under Omega-Regular Constraints. CONCUR 2018: 8:1-8:18.

[3] Emmanuel Filiot, Raffaella Gentilini, Jean-François Raskin: Rational Synthesis Under Imperfect Information. LICS 2018: 422-431.

[4] Krishnendu Chatterjee, Petr Novotný, Guillermo A. Pérez, Jean-François Raskin, Dorde Zikelic:Optimizing Expectation with Guarantees in POMDPs. AAAI 2017: 3725-3732

[5] Raphaël Berthon, Mickael Randour, Jean-François Raskin: Threshold Constraints with Guarantees for Parity Objectives in Markov Decision Processes. ICALP 2017: 121:1-121:15

[6] Jan Kretínský, Tobias Meggendorfer: Conditional Value-at-Risk for Reachability and Mean Payoff in Markov Decision Processes. LICS 2018: 609-618

[7] Tomás Brázdil, Krishnendu Chatterjee, Jan Kretínský, Viktor Toman: Strategy Representation by Decision Trees in Reactive Synthesis. TACAS (1) 2018: 385-407

[8] Edon Kelmendi, Julia Krämer, Jan Kretínský, Maximilian Weininger: Value Iteration for Simple Stochastic Games: Stopping Criterion and Learning Algorithm. CAV (1) 2018: 623-642

[9] Jan Kretínský, Tobias Meggendorfer: Efficient Strategy Iteration for Mean Payoff in Markov Decision Processes. ATVA 2017: 380-399

[10] Pranav Ashok, Krishnendu Chatterjee, Przemyslaw Daca, Jan Kretínský, Tobias Meggendorfer: Value Iteration for Long-Run Average Reward in Markov Decision Processes. CAV (1) 2017: 201-221

[11] Krishnendu Chatterjee, Zuzana Kretínská, Jan Kretínský: Unifying Two Views on Multiple Mean-Payoff Objectives in Markov Decision Processes. Logical Methods in Computer Science 13(2) (2017)

[12] David Klaska, Antonín Kucera, Tomás Lamser, Vojtech Rehák: Automatic Synthesis of Efficient Regular Strategies in Adversarial Patrolling Games. AAMAS 2018: 659-666

[13] Tomás Brázdil, Antonín Kucera, Vojtech Rehák: Solving Patrolling Problems in the Internet Environment. IJCAI 2018: 121-127

[14] Tomás Brázdil, Krishnendu Chatterjee, Antonín Kucera, Petr Novotný, Dominik Velan, Florian Zuleger: Efficient Algorithms for Asymptotic Bounds on Termination Time in VASS. LICS 2018: 185-194

[15] Tomás Brázdil, Krishnendu Chatterjee, Vojtech Forejt, Antonín Kucera: Trading performance for stability in Markov decision processes. J. Comput. Syst. Sci. 84: 144-170 (2017)

[16] Christel Baier, Clemens Dubslaff, Lubos Korenciak, Antonín Kucera, Vojtech Rehák: Synthesis of Optimal Resilient Control Strategies. ATVA 2017: 417-434

[17] Christel Baier, Clemens Dubslaff, Lubos Korenciak, Antonín Kucera, Vojtech Rehák: Mean-Payoff Optimization in Continuous-Time Markov Chains with Parametric Alarms. QEST 2017: 190-206

[18] Krishnendu Chatterjee, Martin Chmelik, Ufuk Topcu: Sensor Synthesis for POMDPs with Reachability Objectives. ICAPS 2018: 47-55

[19] Krishnendu Chatterjee, Monika Henzinger, Veronika Loitzenbauer, Simin Oraee, Viktor Toman: Symbolic Algorithms for Graphs and Markov Decision Processes with Fairness Objectives. CAV (2) 2018: 178-197

[20] Krishnendu Chatterjee, Amir Kafshdar Goharshady, Rasmus Ibsen-Jensen, Yaron Velner: Ergodic Mean-Payoff Games for the Analysis of Attacks in Crypto-Currencies. CONCUR 2018: 11:1-11:17

[21] Krishnendu Chatterjee, Adrián Elgyütt, Petr Novotný, Owen Rouillé: Expectation Optimization with Probabilistic Guarantees in POMDPs with Discounted-Sum Objectives. IJCAI 2018: 4692-4699

[22] Krishnendu Chatterjee, Hongfei Fu, Amir Kafshdar Goharshady, Nastaran Okati: Computational Approaches for Stochastic Shortest Path on Succinct MDPs. IJCAI 2018: 4700-4707

[23] Romain Brenguier, Jean-François Raskin, Ocan Sankur: Assume-admissible synthesis. Acta Inf. 54(1): 41-83 (2017).

[24] Aaron Bohy, Véronique Bruyère, Jean-François Raskin, Nathalie Bertrand: Symblicit algorithms for mean-payoff and shortest path in monotonic Markov decision processes. Acta Inf. 54(6): 545-587 (2017)

[25] Véronique Bruyère, Emmanuel Filiot, Mickael Randour, Jean-François Raskin: Meet your expectations with guarantees: Beyond worst-case synthesis in quantitative games. Inf. Comput. 254: 259-295 (2017)

[26] Nicolas Basset, Ismaël Jecker, Arno Pauly, Jean-François Raskin, Marie van den Bogaard: Beyond Admissibility: Dominance Between Chains of Strategies. CSL 2018: 10:1-10:22

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