finite state Markov decision processes
Multi-Objective Markov Decision Processes for Data-Driven Decision Support
... continuous state features, thus allowing us to use the MOMDP framework to analyze continuous-valued sequential ...the decision-maker to revisit action selection at each decision point in light of new ...
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Simplex Algorithm for Countable state Discounted Markov Decision Processes
... discounted Markov Decision Processes (MDPs) with countably-infinite state spaces, finite action spaces, and unbounded ...countably-infinite state spaces and unbounded rewards, we ...
36
Compositional reasoning for weighted Markov decision processes
... weighted Markov Decision Processes, ...given state, although in general uncountable, in a finite-state wMDP can be generated as the convex-closure of a finite number of ...
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On the relationship between satisfiability and partially observable Markov decision processes
... and decision- theoretic planning in finite horizon partially observable Markov decision processes (POMDPs) are all PSPACE-Complete ...the state spaces they can tackle is ...
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Markov decision processes with uncertain parameters
... of Markov decision problems are explored. We consider state-of-the-art work and models such as those defined in [GLD00, FV97, SL73, WED94, DM10] and present own research on the ...of ...
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Planning in discrete and continuous Markov decision processes by probabilistic programming
... the state is the type of visible objects; in this case the state grows over time when new objects are observed or shrink when objects are removed without uncovering new ...the state transition model, ...
16
Some contributions to Markov decision processes
... In Chapter 2, we systematically investigate a constrained absorbing MDP with expected total cost criterion and possibly unbounded (from both above and below) cost functions. We apply the convex analytic approach to ...
160
On the Complexity of Reachability in Parametric Markov Decision Processes
... Finally, pMDPs are interesting generalisations of other models: [37] shows that parameter synthesis in pMCs is equivalent to the synthesis of finite-state controllers (with a-priori fixed bounds) of ...
17
Approximate Newton Methods for Policy Search in Markov Decision Processes
... The focus of this paper is on policy search methods, which are a family of algorithms that have proven extremely popular in recent years, and which have numerous desirable properties that make them attractive in ...
51
Strategy improvement algorithm for singularly perturbed discounted Markov decision processes
... Finite state and action Markov decision process (MDPs for short) are dynamic, stochastic, systems controlled by controller, sometimes referred to as “decision ...
7
Sufficient Markov Decision Processes.
... any decision process can be made into an MDP by concatenating data over multiple decision points (see Section ...a decision process into the MDP framework in this way can lead to high-dimensional ...
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State Clustering in Markov Decisions Processes with an Application in Information Sharing
... a Markov decision process to prove that a cyclic order up to policy for the supplier is optimal and has a finite steady state average cost for the discounted and average cost ...
153
Performance Guarantees for Homomorphisms beyond Markov Decision Processes
... a finite state POMDP then our re- sults provide the performance-loss guarantee by represent- ing a belief-state based value function of the POMDP by a state-based value ...
8
Randomized and Relaxed Strategies in Continuous-Time Markov Decision Processes
... Theorem 5 about sufficiency of Poisson-related strategies can be a starting point for involving the results in discrete-time Markov decision processes (DTMDP) like the linear programming approach ...
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Policy-Gradient Algorithms for Partially Observable Markov Decision Processes
... added state where a reward of 1 is received prior to the agent being taken back to the start ...start state, for the declare goal action in the wrong ...
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LIMITING PROBABILITY TRANSITION MATRIX OF A CONDENSED FIBONACCI TREE
... a finite one dimensional random walk with equal probabilities of one step to the right or two step to the left except near the ...whose markov chain or equivalently, the corresponding digraph, can be ...
10
Finite State Transducers Approximating Hidden Markov Models
... We then build the union uS i of all initial subsequences Si and the union uS~n of all extended middle subsequences S,e=, and formulate a preliminary sentence model: uS ° = ~S, uS°~* 14 i[r] ...
8
The SIS epidemic model with Markovian switching
... As a slightly more realistic example to illustrate the two state case, we consider Streptococcus pneumoniae (S. pneumoniae) amongst children under 2 years in Scotland. This may display a phenomenon called capsular ...
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Bisimulation and Logical Preservation for Continuous-Time Markov Decision Processes
... For a specific subclass of sets of paths: lift the argument to the quotient space.. Summary Related Work[r] ...
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Partially Observable Markov Decision Processes for Prostate Cancer Screening.
... medical decision making are reviewed in Schaefer et ...medical decision making was proposed by Smallwood et ...information state diagram to visualize the belief ...medical decision making ...
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