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ORCIDISAIM 2008: Fort Lauderdale, Florida, USA
- International Symposium on Artificial Intelligence and Mathematics, ISAIM 2008, Fort Lauderdale, Florida, USA, January 2-4, 2008. 2008
Papers accepted to the main technical program
- Andreas Alexander Albrecht, Peter C. R. Lane, Kathleen Steinhöfel:
Estimating the Number of Local Maxima for k-SAT Instances. - Carlos Ansótegui, Ramón Béjar, Cèsar Fernández, Carles Mateu:
Hard SAT and CSP instances with Expander Graphs. - Vincent Aravantinos, Ricardo Caferra, Nicolas Peltier:
More Flexible Term Schematisations via Extended Primal Grammars. - Manuel Atencia, W. Marco Schorlemmer:
Formalising Interaction-Situated Semantic Alignment: The Communication Product. - Michael Biggs, Ali Ghodsi, Dana F. Wilkinson, Michael H. Bowling:
Scalable Action Respecting Embedding. - Branislav Kveton, Jia Yuan Yu, Georgios Theocharous, Shie Mannor:
A Lazy Approach to Online Learning with Constraints. - Emma Brunskill, Leslie Pack Kaelbling, Tomás Lozano-Pérez, Nicholas Roy:
Continuous-State POMDPs with Hybrid Dynamics. - Douglas Cenzer, Jeffrey B. Remmel:
A Connection between Cantor-Bendixson Derivatives and the Well-Founded Semantics of Logic Programs. - Fabio Cuzzolin:
An Interpretation of Consistent Belief Functions in Terms of Simplicial Complexes. - Fabio Cuzzolin:
Boolean and Matroidal Independence in Uncertainty Theory. - Bistra Dilkina, Carla P. Gomes, Ashish Sabharwal:
Tradeoffs in Backdoors: Inconsistency Detection, Dynamic Simplification, and Preprocessing. - Pinar Donmez, Jaime G. Carbonell:
Paired Sampling in Density-Sensitive Active Learning. - Finale Doshi, Joelle Pineau, Nicholas Roy:
Reinforcement Learning with Limited Reinforcement: Using Bayes Risk for Active Learning in POMDPs. - P. Alex Dow, Richard E. Korf:
Best-First Search with Maximum Edge Cost Functions. - Yu Fan, Christian R. Shelton:
Sampling for Approximate Inference in Continuous Time Bayesian Networks. - Alireza Farhangfar, Russell Greiner, Martin Zinkevich:
A Fast Way to Produce Optimal Fixed-Depth Decision Trees. - Andrew Guillory, Jeff A. Bilmes:
Practical Methods for Exploiting Bounds on Change in the Margin. - Erik Halvorson, Ronald Parr:
Planning Aims for a Network of Horizontal and Overhead Sensors. - Jingrui He, Jaime G. Carbonell:
Rare Class Discovery Based on Active Learning. - Hengshuai Yao, Zhi-Qiang Liu:
Minimal Residual Approaches for Policy Evaluation in Large Sparse Markov Chains. - Nathalie Japkowicz, Pritika Sanghi, Peter E. Tischer:
Classifier Utility Visualization by Distance-Preserving Projection of High Dimensional Performance D. - Kin Fai Kan, Christian R. Shelton:
Solving Structured Continuous-Time Markov Decision Processes. - Hoyt A. Koepke, Bertrand S. Clarke:
A Bayesian Approach to Cluster Validation. - Lukas Kroc, Bart Selman, Ashish Sabharwal:
Leveraging Belief Propagation, Backtrack Search, and Statistics for Model Counting. - Marina Langlois, Dhruv Mubayi, Robert H. Sloan, György Turán:
Combinatorial problems for Horn clauses. - Lihong Li, Michael L. Littman:
Efficient Value-Function Approximation via Online Linear Regression. - Dennis Perez, Prashant Doshi:
Approximate Solutions of Interactive POMDPs Using Point Based Value Iteration. - Franz Pernkopf, Jeff A. Bilmes:
Order-based Discriminative Structure Learning for Bayesian Network Classifiers. - Marek Petrik, Shlomo Zilberstein:
A Successive Approximation Algorithm for Coordination Problems. - Gregory M. Provan:
Approximation Techniques for Space-Efficient Compilation in Abductive Inference. - Emmanuel Rachelson, Frédérick Garçia, Patrick Fabiani:
Extending the Bellman equation for MDPs to continuous actions and cont. time in the discounted case. - Matthew R. Rudary, Satinder Singh:
Predictive Linear-Gaussian Models of Dynamical Systems with Vector-Valued Actions and Observations. - Emad Saad:
On the Relationship between Hybrid Probabilistic Logic Programs and Stochastic Satisfiability. - T. K. Satish Kumar:
Lifting Techniques for Weighted Constraint Satisfaction Problems. - Sajjad Ahmed Siddiqi, Jinbo Huang:
Probabilistic Sequential Diagnosis by Compilation. - Tomás Singliar, Milos Hauskrecht:
Approximation Strategies for Routing in Stochastic Dynamic Networks. - Siddharth Srivastava, Neil Immerman, Shlomo Zilberstein:
Using Abstraction for Generalized Planning. - Erik Talvitie, Britton Wolfe, Satinder Singh:
Building Incomplete but Accurate Models. - Allen Van Gelder:
Verifying RUP Proofs of Propositional Unsatisfiability.
Papers of the Keynote Speakers
- Francesca Rossi:
Preferences, Constraints, Uncertainty, and Multi-Agent Scenarios. - Naftali Tishby:
Extracting Relevant Information from Samples.
Papers of the Special Session on Logic in Artificial Intelligence
- Howard A. Blair, David W. Jakel, Robert J. Irwin, Angel J. Rivera:
Hybrid Programs: Symmetrically Combining Natively Discrete and Continuous Truth-values. - Alex Bochman:
Default Logic Generalized and Simplified. - Thomas Eiter, Thomas Krennwallner, Roman Schindlauer, Giovambattista Ianni:
Exploiting Conjunctive Queries in Description Logic Programs. - Melvin Fitting:
Explicit Logics of Knowledge and Conservativity. - Michael Kaminski:
A Non-Preferential Semantics of Non-Monotonic Modal Logic. - Johann A. Makowsky:
From Hilbert's Program to a Logic Toolbox. - Veena S. Mellarkod, Michael Gelfond
, Yuanlin Zhang:
Integrating Answer Programming and Constraint Logic Programming. - Ilkka Niemelä:
Stable Models and Difference Logic. - Jeffrey B. Remmel:
A Mathematician Looks at Answer Set Programming. - John S. Schlipf, Marc Denecker:
Complexity of First Order ID-Logic. - Marian Srebrny, Mateusz Srebrny, Lidia Stepien:
SAT as a Programming Environment for Linear Algebra and Cryptanalysis. - Miroslaw Truszczynski, Stefan Woltran:
Hyperequivalence of Programs and Operators.
Papers of the Special Session on Computation and Social Choice
- Vincent Conitzer:
Comparing Multiagent Systems Research in Combinatorial Auctions and Voting. - John N. Hooker:
Optimality Conditions for Distributive Justice. - Toby Walsh:
Complexity Issues in Preference Elicitation and Manipulation.
Papers of the Special Session on Effective Exploration in Active Learning and Reinforcement Learning
- Sanjoy Dasgupta, Daniel J. Hsu, Claire Monteleoni:
A General Agnostic Active Learning Algorithm. - Joelle Pineau, Stéphane Ross, Brahim Chaib-draa:
Bayes-Adaptive POMDPs: A New Perspective on the Explore-Exploit Tradeoff in Partially Observable Domains. - Pascal Poupart, Nikos Vlassis:
Model-based Bayesian Reinforcement Learning in Partially Observable Domains. - Irina Rish, Gerald Tesauro:
Active Collaborative Prediction with Maximum Margin Matrix Factorization. - Alexander L. Strehl:
Probably Approximately Correct (PAC) Exploration in Reinforcement Learning.
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