A model for reasoning about persistence and causation
Computational Intelligence
Practical Issues in Temporal Difference Learning
Machine Learning
TD-Gammon, a self-teaching backgammon program, achieves master-level play
Neural Computation
Temporal difference learning and TD-Gammon
Communications of the ACM
A counterexample to temporal differences learning
Neural Computation
Markov Decision Processes: Discrete Stochastic Dynamic Programming
Markov Decision Processes: Discrete Stochastic Dynamic Programming
Introduction to Linear Optimization
Introduction to Linear Optimization
Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
Neuro-Dynamic Programming
Variable Resolution Discretization in Optimal Control
Machine Learning
Computing Factored Value Functions for Policies in Structured MDPs
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Approximating MAP using Local Search
UAI '01 Proceedings of the 17th Conference in Uncertainty in Artificial Intelligence
Context-specific multiagent coordination and planning with factored MDPs
Eighteenth national conference on Artificial intelligence
Greedy linear value-approximation for factored Markov decision processes
Eighteenth national conference on Artificial intelligence
Dynamic Programming
Approximate solutions to markov decision processes
Approximate solutions to markov decision processes
Selecting approximately-optimal actions in complex structured domains
Selecting approximately-optimal actions in complex structured domains
The Linear Programming Approach to Approximate Dynamic Programming
Operations Research
Planning under uncertainty in complex structured environments
Planning under uncertainty in complex structured environments
On Constraint Sampling in the Linear Programming Approach to Approximate Dynamic Programming
Mathematics of Operations Research
Dynamic programming for structured continuous Markov decision problems
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
Metrics for finite Markov decision processes
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
Solving factored MDPs with continuous and discrete variables
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
Learning basis functions in hybrid domains
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
Learning representation and control in continuous Markov decision processes
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
Samuel meets Amarel: automating value function approximation using global state space analysis
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 2
Value-function approximations for partially observable Markov decision processes
Journal of Artificial Intelligence Research
Efficient solution algorithms for factored MDPs
Journal of Artificial Intelligence Research
Generalizing plans to new environments in relational MDPs
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Max-norm projections for factored MDPs
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
An MCMC approach to solving hybrid factored MDPs
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Exploiting structure in policy construction
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
A reinforcement learning approach to job-shop scheduling
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Planning under continuous time and resource uncertainty: a challenge for AI
UAI'02 Proceedings of the Eighteenth conference on Uncertainty in artificial intelligence
Bucket elimination: a unifying framework for probabilistic inference
UAI'96 Proceedings of the Twelfth international conference on Uncertainty in artificial intelligence
Solving MAP exactly using systematic search
UAI'03 Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence
Adaptive multi-robot wide-area exploration and mapping
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 1
Factored value iteration converges
Acta Cybernetica
Factored temporal difference learning in the new ties environment
Acta Cybernetica
A heuristic search approach to planning with continuous resources in stochastic domains
Journal of Artificial Intelligence Research
Computational approaches to reachability analysis of stochastic hybrid systems
HSCC'07 Proceedings of the 10th international conference on Hybrid systems: computation and control
Planning in stochastic domains for multiple agents with individual continuous resource state-spaces
Autonomous Agents and Multi-Agent Systems
A framework and a mean-field algorithm for the local control of spatial processes
International Journal of Approximate Reasoning
Robust optimization for hybrid MDPs with state-dependent noise
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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Efficient representations and solutions for large decision problems with continuous and discrete variables are among the most important challenges faced by the designers of automated decision support systems. In this paper, we describe a novel hybrid factored Markov decision process (MDP) model that allows for a compact representation of these problems, and a new hybrid approximate linear programming (HALP) framework that permits their efficient solutions. The central idea of HALP is to approximate the optimal value function by a linear combination of basis functions and optimize its weights by linear programming. We analyze both theoretical and computational aspects of this approach, and demonstrate its scale-up potential on several hybrid optimization problems.