Stochastic dynamic programming with factored representations
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Craig Boutilier | Richard Dearden | Moisés Goldszmidt | M. Goldszmidt | Craig Boutilier | R. Dearden
[1] Jesse Hoey,et al. SPUDD: Stochastic Planning using Decision Diagrams , 1999, UAI.
[2] Craig Boutilier,et al. Decision-Theoretic Planning: Structural Assumptions and Computational Leverage , 1999, J. Artif. Intell. Res..
[3] Thomas G. Dietterich. The MAXQ Method for Hierarchical Reinforcement Learning , 1998, ICML.
[4] Ronen I. Brafman,et al. Structured Reachability Analysis for Markov Decision Processes , 1998, UAI.
[5] Kee-Eung Kim,et al. Solving Very Large Weakly Coupled Markov Decision Processes , 1998, AAAI/IAAI.
[6] Doina Precup,et al. Theoretical Results on Reinforcement Learning with Temporally Abstract Options , 1998, ECML.
[7] Konkoly Thege. Multi-criteria Reinforcement Learning , 1998 .
[8] R. Sutton,et al. Theoretical Results on Reinforcement Learning with Temporally Abstract Behaviors , 1998 .
[9] Satinder P. Singh,et al. How to Dynamically Merge Markov Decision Processes , 1997, NIPS.
[10] Ronen I. Brafman,et al. Prioritized Goal Decomposition of Markov Decision Processes: Toward a Synthesis of Classical and Decision Theoretic Planning , 1997, IJCAI.
[11] Robert Givan,et al. Model Minimization, Regression, and Propositional STRIPS Planning , 1997, IJCAI.
[12] Robert Givan,et al. Model Reduction Techniques for Computing Approximately Optimal Solutions for Markov Decision Processes , 1997, UAI.
[13] Craig Boutilier,et al. Correlated Action Effects in Decision Theoretic Regression , 1997, UAI.
[14] Robert Givan,et al. Model Minimization in Markov Decision Processes , 1997, AAAI/IAAI.
[15] David Poole,et al. The Independent Choice Logic for Modelling Multiple Agents Under Uncertainty , 1997, Artif. Intell..
[16] Craig Boutilier,et al. Abstraction and Approximate Decision-Theoretic Planning , 1997, Artif. Intell..
[17] Craig Boutilier,et al. Computing Optimal Policies for Partially Observable Decision Processes Using Compact Representations , 1996, AAAI/IAAI, Vol. 2.
[18] Craig Boutilier,et al. Context-Specific Independence in Bayesian Networks , 1996, UAI.
[19] Craig Boutilier,et al. The Frame Problem and Bayesian Network Action Representation , 1996, Canadian Conference on AI.
[20] Andrew W. Moore,et al. Reinforcement Learning: A Survey , 1996, J. Artif. Intell. Res..
[21] Craig Boutilier,et al. Approximate Value Trees in Structured Dynamic Programming , 1996, ICML.
[22] John N. Tsitsiklis,et al. Neuro-Dynamic Programming , 1996, Encyclopedia of Machine Learning.
[23] Michael L. Littman,et al. Algorithms for Sequential Decision Making , 1996 .
[24] Craig Boutilier,et al. Process-Oriented Planning and Average-Reward Optimality , 1995, IJCAI.
[25] Nicholas Kushmerick,et al. An Algorithm for Probabilistic Planning , 1995, Artif. Intell..
[26] Leslie Pack Kaelbling,et al. Acting Optimally in Partially Observable Stochastic Domains , 1994, AAAI.
[27] Stuart J. Russell,et al. Control Strategies for a Stochastic Planner , 1994, AAAI.
[28] Craig Boutilier,et al. Using Abstractions for Decision-Theoretic Planning with Time Constraints , 1994, AAAI.
[29] Moisés Goldszmidt,et al. Action Networks: A Framework for Reasoning about Actions and Change under Uncertainty , 1994, UAI.
[30] Martin L. Puterman,et al. Markov Decision Processes: Discrete Stochastic Dynamic Programming , 1994 .
[31] Gerald Tesauro,et al. TD-Gammon, a Self-Teaching Backgammon Program, Achieves Master-Level Play , 1994, Neural Computation.
[32] Drew McDermott,et al. Modeling a Dynamic and Uncertain World I: Symbolic and Probabilistic Reasoning About Change , 1994, Artif. Intell..
[33] Andrew W. Moore,et al. Generalization in Reinforcement Learning: Safely Approximating the Value Function , 1994, NIPS.
[34] R. I. Bahar,et al. Algebraic decision diagrams and their applications , 1993, Proceedings of 1993 International Conference on Computer Aided Design (ICCAD).
[35] David Poole,et al. Probabilistic Horn Abduction and Bayesian Networks , 1993, Artif. Intell..
[36] Leslie Pack Kaelbling,et al. Planning With Deadlines in Stochastic Domains , 1993, AAAI.
[37] Solomon Eyal Shimony,et al. The role of relevance in explanation I: Irrelevance as statistical independence , 1993, Int. J. Approx. Reason..
[38] James E. Smith,et al. Structuring Conditional Relationships in Influence Diagrams , 1993, Oper. Res..
[39] Daniel S. Weld,et al. UCPOP: A Sound, Complete, Partial Order Planner for ADL , 1992, KR.
[40] J. Ross Quinlan,et al. C4.5: Programs for Machine Learning , 1992 .
[41] Edmund M. Clarke,et al. Symbolic Model Checking: 10^20 States and Beyond , 1990, Inf. Comput..
[42] E. Clarke,et al. Symbolic Model Checking : IO * ’ States and Beyond * , 1992 .
[43] David Heckerman,et al. Advances in Probabilistic Reasoning , 1994, Conference on Uncertainty in Artificial Intelligence.
[44] Leslie Pack Kaelbling,et al. Input Generalization in Delayed Reinforcement Learning: An Algorithm and Performance Comparisons , 1991, IJCAI.
[45] David A. McAllester,et al. Systematic Nonlinear Planning , 1991, AAAI.
[46] W. Lovejoy. A survey of algorithmic methods for partially observed Markov decision processes , 1991 .
[47] Richard S. Sutton,et al. Integrated Architectures for Learning, Planning, and Reacting Based on Approximating Dynamic Programming , 1990, ML.
[48] Ross D. Shachter,et al. Dynamic programming and influence diagrams , 1990, IEEE Trans. Syst. Man Cybern..
[49] Drew V. Mcdermott,et al. Projecting plans for uncertain worlds , 1990 .
[50] Judea Pearl,et al. Probabilistic reasoning in intelligent systems - networks of plausible inference , 1991, Morgan Kaufmann series in representation and reasoning.
[51] D. Bertsekas,et al. Adaptive aggregation methods for infinite horizon dynamic programming , 1989 .
[52] Keiji Kanazawa,et al. A model for reasoning about persistence and causation , 1989 .
[53] Ronald A. Howard,et al. Readings on the Principles and Applications of Decision Analysis , 1989 .
[54] Marcel Schoppers,et al. Universal Plans for Reactive Robots in Unpredictable Environments , 1987, IJCAI.
[55] David Chapman,et al. Planning for Conjunctive Goals , 1987, Artif. Intell..
[56] Dimitri P. Bertsekas,et al. Dynamic Programming: Deterministic and Stochastic Models , 1987 .
[57] Ross D. Shachter. Evaluating Influence Diagrams , 1986, Oper. Res..
[58] Randal E. Bryant,et al. Graph-Based Algorithms for Boolean Function Manipulation , 1986, IEEE Transactions on Computers.
[59] Paul J. Schweitzer,et al. Iterative Aggregation-Disaggregation Procedures for Discounted Semi-Markov Reward Processes , 1985, Oper. Res..
[60] A. Prasad Sistla,et al. Automatic verification of finite state concurrent system using temporal logic specifications: a practical approach , 1983, POPL '83.
[61] John McCarthy,et al. SOME PHILOSOPHICAL PROBLEMS FROM THE STANDPOINT OF ARTI CIAL INTELLIGENCE , 1987 .
[62] R. L. Keeney,et al. Decisions with Multiple Objectives: Preferences and Value Trade-Offs , 1977, IEEE Transactions on Systems, Man, and Cybernetics.
[63] M. Puterman,et al. Modified Policy Iteration Algorithms for Discounted Markov Decision Problems , 1978 .
[64] Edward J. Sondik,et al. The Optimal Control of Partially Observable Markov Processes over the Infinite Horizon: Discounted Costs , 1978, Oper. Res..
[65] Jerome A. Feldman,et al. Decision Theory and Artificial Intelligence II: The Hungry Monkey , 1977, Cogn. Sci..
[66] Richard Waldinger,et al. Achieving several goals simultaneously , 1977 .
[67] Ronald L. Rivest,et al. Constructing Optimal Binary Decision Trees is NP-Complete , 1976, Inf. Process. Lett..
[68] Earl D. Sacerdoti,et al. The Nonlinear Nature of Plans , 1975, IJCAI.
[69] Edsger W. Dijkstra,et al. Guarded commands, nondeterminacy and formal derivation of programs , 1975, Commun. ACM.
[70] Edward J. Sondik,et al. The Optimal Control of Partially Observable Markov Processes over a Finite Horizon , 1973, Oper. Res..
[71] Richard Fikes,et al. STRIPS: A New Approach to the Application of Theorem Proving to Problem Solving , 1971, IJCAI.
[72] Donald Michie,et al. Machine Intelligence 4 , 1970 .
[73] R. Bellman. Dynamic programming. , 1957, Science.
[74] J. Hartmanis,et al. Algebraic Structure Theory Of Sequential Machines , 1966 .
[75] R. Howard. Dynamic Programming and Markov Processes , 1960 .