The Tenth International Symposium on Artificial Intelligence and Mathematics
| # Fort Lauderdale, Florida January 2-4, 2008
| Rasa 3 © Marjorie Mikasen 2000

| # Proceedings The electronic proceedings for ISAIM 2008 are now available. Note that papers accepted at ISAIM 2008 are not published in formal proceedings and not subject to copyright restrictions. All authors retain the copyright to their papers. ## List of Papers Below, we provide the lists of, and the links to, papers accepted to the main technical program, papers by the Keynote Speakers, and papers by the invited speakers of the Special Sessions. ## Papers accepted to the main technical program Estimating the Number of Local Maxima for k-SAT Instances Andreas Albrecht, Peter Lane, Kathleen Steinhoefel Hard SAT and CSP instances with Expander Graphs Carlos Ansotegui, Ramon Bejar, Cesar Fernandez, Carles Mateu More Flexible Term Schematisations via Extended Primal Grammars Vincent Aravantinos, Ricardo Caferra, Nicolas Peltier Formalising Interaction-Situated Semantic Alignment: The Communication Product Manuel Atencia, Marco Schorlemmer Scalable Action Respecting Embedding Michael Biggs, Ali Ghodsi, Dana Wilkinson, Michael Bowling A Lazy Approach to Online Learning with Constraints Kveton Branislav, Jia Yuan Yu, Georgios Theocharous, Shie Mannor Continuous-State POMDPs with Hybrid Dynamics Emma Brunskill, Leslie Kaelbling, Tomas Lozano-Perez, Nicholas Roy A Connection between Cantor-Bendixson Derivatives and the Well-Founded Semantics of Logic Programs Douglas Cenzer, Jeffrey Remmel An Interpretation of Consistent Belief Functions in Terms of Simplicial Complexes Fabio Cuzzolin Boolean and Matroidal Independence in Uncertainty Theory Fabio Cuzzolin Tradeoffs in Backdoors: Inconsistency Detection, Dynamic Simplification, and Preprocessing Bistra Dilkina, Carla Gomes, Ashish Sabharwal Paired Sampling in Density-Sensitive Active Learning Pinar Donmez, Jaime Carbonell Reinforcement Learning with Limited Reinforcement: Using Bayes Risk for Active Learning in POMDPs Finale Doshi, Joelle Pineau, Nicholas Roy Best-First Search with Maximum Edge Cost Functions P. Alex Dow, Richard Korf Sampling for Approximate Inference in Continuous Time Bayesian Networks Yu Fan, Christian Shelton A Fast Way to Produce Optimal Fixed-Depth Decision Trees Alireza Farhangfar, Russell Greiner, Martin Zinkevich Practical Methods for Exploiting Bounds on Change in the Margin Andrew Guillory, Jeff Bilmes Planning Aims for a Network of Horizontal and Overhead Sensors Erik Halvorson, Ronald Parr Rare Class Discovery Based on Active Learning Jingrui He, Jaime Carbonell Minimal Residual Approaches for Policy Evaluation in Large Sparse Markov Chains Yao Hengshuai, Liu Zhiqiang Classifier Utility Visualization by Distance-Preserving Projection of High Dimensional Performance D Nathalie Japkowicz, Pritika Sanghi, Peter Tischer Solving Structured Continuous-Time Markov Decision Processes Kin Fai Kan, Christian Shelton A Bayesian Approach to Cluster Validation Hoyt Koepke, Bertrand Clarke Leveraging Belief Propagation, Backtrack Search, and Statistics for Model Counting Lukas Kroc, Bart Selman, Ashish Sabharwal Combinatorial problems for Horn clauses Marina Langlois, Dhruv Mubayi, Robert Sloan, Gyorgy Turan Efficient Value-Function Approximation via Online Linear Regression Lihong Li, Michael Littman Approximate Solutions of Interactive POMDPs Using Point Based Value Iteration Dennis Perez, Prashant Doshi Order-based Discriminative Structure Learning for Bayesian Network Classifiers Franz Pernkopf, Jeff Bilmes A Successive Approximation Algorithm for Coordination Problems Marek Petrik, Shlomo Zilbertstein Approximation Techniques for Space-Efficient Compilation in Abductive Inference Gregory Provan Extending the Bellman equation for MDPs to continuous actions and cont. time in the discounted case Emmanuel Rachelson, Frédérick Garcia, Patrick Fabiani Predictive Linear-Gaussian Models of Dynamical Systems with Vector-Valued Actions and Observations Matthew Rudary, Satinder Singh On the Relationship between Hybrid Probabilistic Logic Programs and Stochastic Satisfiability Emad Saad Lifting Techniques for Weighted Constraint Satisfaction Problems T. K. Satish Kumar Probabilistic Sequential Diagnosis by Compilation Sajjad Siddiqi, Jinbo Huang Approximation Strategies for Routing in Stochastic Dynamic Networks Tomas Singliar, Milos Hauskrecht Using Abstraction for Generalized Planning Siddharth Srivastava, Neil Immerman, Shlomo Zilbertstein Building Incomplete but Accurate Models Erik Talvitie, Britton Wolfe, Satinder Singh Verifying RUP Proofs of Propositional Unsatisfiability Allen Van Gelder ## Papers of the Keynote Speakers Preferences, Constraints, Uncertainty, and Multi-Agent Scenarios Francesca Rossi Extracting Relevant Information from Samples (Slides of invited talk and post-conference paper) Naftali Tishby ## Papers of the Special Session on Logic in Artificial Intelligence Hybrid Programs: Symmetrically Combining Natively Discrete and Continuous Truth-values H.A. Blair, D.W. Jakel, R.J. Irwin, A.J. Rivera Default Logic Generalized and Simplified Alex Bochman Exploiting Conjunctive Queries in Description Logic Programs Thomas Eiter, Thomas Krennwallner, Roman Schindlauer, Giovambattista Ianni Explicit Logics of Knowledge and Conservativity Melvin Fitting A Non-Preferential Semantics of Non-Monotonic Modal Logic Michael Kaminski From Hilbert's Program to a Logic Toolbox Johann A. Makowsky Integrating Answer Programming and Constraint Logic Programming Veena S. Mellarkod, Michael Gelfond, Yuanlin Zhang Stable Models and Difference Logic Ilkka Niemela A Mathematician Looks at Answer Set Programming Jeffrey B. Remmel Complexity of First Order ID-Logic John S. Schlipf, Marc Denecker SAT as a Programming Environment for Linear Algebra and Cryptanalysis Marian Srebrny, Mateusz Srebrny, Lidia Stepien Hyperequivalence of Programs and Operators Miroslaw Truszczynski, Stefan Woltran ## Papers of the Special Session on Computation and Social Choice Comparing Multiagent Systems Research in Combinatorial Auctions and Voting Vincent Conitzer Optimality Conditions for Distributive Justice John Hooker Complexity Issues in Preference Elicitation and Manipulation Toby Walsh ## Papers of the Special Session on Effective Exploration in Active Learning and Reinforcement Learning A General Agnostic Active Learning Algorithm Sanjoy Dasgupta, Daniel Hsu, Claire Monteleoni Bayes-Adaptive POMDPs: A New Perspective on the Explore-Exploit Tradeoff in Partially Observable Domains Joelle Pineau, Stephane Ross, Brahim Chaib-draa Model-based Bayesian Reinforcement Learning in Partially Observable Domains Pascal Poupart, Nikos Vlassis Active Collaborative Prediction with Maximum Margin Matrix Factorization Irina Rish, Gerald Tesauro Probably Approximately Correct (PAC) Exploration in Reinforcement Learning Alexander L. Strehl

Last updated: December 12, 2007.