IJCAI-JAIR Best Paper Prize


The Annual IJCAI-JAIR Best Paper Prize is awarded to an outstanding paper published in JAIR in the preceding five calendar years. The prize committee is comprised of associate editors and members of the JAIR Advisory Board; their decision is based on both the significance of the paper and the quality of presentation. The recipient(s) of the award receives a prize of US$500 (to be split amongst the authors of a co-authored paper). Funding for this award was provided by the International Joint Conferences on Artificial Intelligence.


The 2013 Prize Committee selected the following paper that provides strong theoretical results for the problem of online stochastic optimization under partial observability. The authors identify an important subclass of this problem that satisfies the property of adaptive submodularity. For this class, the authors demonstrate that approximation bounds can be achieved using a simple adaptive greedy policy. Importantly, this subclass is general enough to cover various application domains, such as active learning, stochastic coverage problems, and viral marketing. The theoretical results, corroborated by empirical evidence, suggest that the concept of adaptive submodularity is very useful in stochastic optimization problems.

The prize will be announced at the IJCAI '13 awards ceremony.

2013 Prize: Daniel Golovin and Andreas Krause (2011) "Adaptive Submodularity: Theory and Applications in Active Learning and Stochastic Optimization", Volume 42, 427-486.


2012 Prize: H. Palacios and H. Geffner (2009) "Compiling Uncertainty Away in Conformant Planning Problems with Bounded Width", Volume 35, 623-675.

2012 Honorable Mention: A. Krause and C. Guestrin (2009) "Optimal Value of Information in Graphical Models", Volume 35, 557-591.


2011 Prize: N. Nisan and A. Ronen (2007) "Computationally Feasible VCG Mechanisms" Volume 29, 19-47.

2011 Honorable Mention: A. Fern, S. Yoon and R. Givan (2006) "Approximate Policy Iteration with a Policy Language Bias: Solving Relational Markov Decision Processes", Volume 25, 75-118.


2010 Prize: L. Xu, F. Hutter, H. Hoos, and K. Leyton-Brown (2008) "SATzilla: Portfolio-based Algorithm Selection for SAT", Volume 32, 565-606.

2010 Honorable Mention: S. Ponzetto and M. Strube (2007) "Knowledge Derived From Wikipedia For Computing Semantic Relatedness", Volume 30, 181-212.


2009 Prize: C. Boutilier, R. Brafman, C. Domshlak, H. Hoos, and D. Poole (2004) "CP-nets: A Tool for Representing and Reasoning with Conditional Ceteris Paribus Preference Statements", Volume 21, pages 135-191.

2009 Honorable Mention: M. Helmert (2006) "The Fast Downward Planning System", Volume 26, pages 191-246.


2008 Prize: G. Gottlob, G. Greco and F. Scarcello (2005) "Pure Nash Equilibria: Hard and Easy Games", Volume 24, pages 357-406.

2008 Honorable Mention: P. Beame, H. Kautz and A. Sabharwal (2004) "Towards Understanding and Harnessing the Potential of Clause Learning", Volume 22, pages 319-351.


2007 Prize: Guestrin, C., Koller, D., Parr, R. and Venkataraman, S. (2003) "Efficient Solution Algorithms for Factored MDPs", 19, 399 - 468.

2007 Honorable Mention: Felner, A., Korf, R.E. and Hanan, S. (2004) "Additive Pattern Database Heuristics", 22, 279-318.


2006 Prize: Darwiche, A. and Marquis, P. (2002) "A Knowledge Compilation Map", 17, 229 - 264.

2006 Honorable Mention: Ginsberg, M.L. (2001) "GIB: Imperfect Information in a Computationally Challenging Game", 14, 303-358.


2005 Prize: Hoffmann, J. and Nebel, B. (2001) "The FF Planning System: Fast Plan Generation Through Heuristic Search", 14, 253 - 302.

2005 Honorable Mention: Cheng, J. and Druzdzel, M.J. (2000) "AIS-BN: An Adaptive Importance Sampling Algorithm for Evidential Reasoning in Large Bayesian Networks", 13, 155-188.


2004 Prize: Ygge, F. and Akkermans, H. (1999) "Decentralized Markets versus Central Control: A Comparative Study", 11, 301-333.

2004 Honorable Mention: Fox, D., Burgard, W. and Thrun, S. (1999) "Markov Localization for Mobile Robots in Dynamic Environments", 11, 391-427.


2003 Prize: Dietterich, T.G. (2000) "Hierarchical Reinforcement Learning with the MAXQ Value Function Decomposition", 13, 227-303.

2003 Honorable Mention: Littman, M.L., Goldsmith, J. and Mundhenk M. (1998) "The Computational Complexity of Probabilistic Planning", 9, 1-36.