Towards Faster Planning with Continuous Resources in Stochastic Domains
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Summary
The experimental evaluation shows that, when run stand-alone, DPFP outperforms other algorithms in terms of its any-time performance, whereas when run as a hybrid, it allows for a significant speedup of a leading continuous resource MDP solver.
- Type
- article
- Published
- 2008-07-13
- Cited by
- 15
- References
- 17
- OpenAlex
- https://openalex.org/W1189345
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:6411264
Keywords
Computer science, Speedup, Markov decision process, Mathematical optimization, Dual (grammatical number)
References
- A Fast Analytical Algorithm for Solving Markov Decision Processes with Real-Valued Resources
- Lazy Approximation for Solving Continuous Finite-Horizon MDPs
- Constrained Markov Decision Processes
- Planning with Continuous Resources in Stochastic Domains
- Stationary Deterministic Policies for Constrained MDPs with Multiple Rewards, Costs, and Discount Factors
- Scaling Up Decision Theoretic Planning to Planetary Rover Problems
- Stochastic dynamic programming with factored representations
- Winning back the CUP for distributed POMDPs: planning over continuous belief spaces
- Least-Squares Policy Iteration
- Planning Under Continuous Time and Resource Uncertainty: A Challenge for AI
- Solving Factored MDPs with Continuous and Discrete Variables
- Non-Linear Stochastic Control in Continuous State Spaces by Exact Integration in Bellman's Equations
- Chapman and Hall
- Dynamic Programming for Structured Continuous Markov Decision Problems
- Dynamic programming for structured continuous Markov decision problems
- Policy Search via Density Estimation
- Planning with Continuous Resources in Stochastic Domains
Cited by
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- Compact parametric models for efficient sequential decision making in high-dimensional, uncertain domains
- Game-Theoretic Patrolling with Dynamic Execution Uncertainty and a Case Study on a Real Transit System
- Algorithms and mechanisms for procuring services with uncertain durations using redundancy
- Provably Efficient Learning with Typed Parametric Models
- Making Good Decisions Quickly
- Goal Probability Analysis in Probabilistic Planning: Exploring and Enhancing the State of the Art
- Revisiting Goal Probability Analysis in Probabilistic Planning
- Risk-Sensitive Stochastic Orienteering Problems for Trip Optimization in Urban Environments
- Planning with Markov Decision Processes: An AI Perspective
- Game-Theoretic Security Patrolling with Dynamic Execution Uncertainty and a Case Study on a Real Transit System
- Contributions à la planification automatique pour la conduite de systèmes autonomes
- ARMOR: Assistant for Randomized Monitoring Over Routes
- Goal Probability Analysis in MDP Probabilistic Planning: Exploring and Enhancing the State of the Art
- Game-theoretic Security Patrolling with Dynamic Execution Uncertainty Game-theoretic Security Patrolling with Dynamic Execution Uncertainty and a Case Study on a Real Transit System 1
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