• Entropy Maximization for Markov Decision Processes Under ...🔍
• An Algebraic Approach to Abstraction in Semi|Markov Decision ...🔍
• discrete|time controlled markov processes with average cost ...🔍
• Fuel in Markov Decision Processes 🔍
• CONSTRAINED MARKOV DECISION PROCESSES VIA ...🔍
• Constrained Markov Decision Processes🔍
• Equivalence of Optimality Criteria for Markov Decision Process and ...🔍
• Linearly|solvable Markov decision problems🔍

Entropy Maximization for Markov Decision Processes Under ...

The maximum entropy of all product MDPs subject to corresponding LTL constraints are unbounded. We bound the expected time until the completion of any task by ...

An Algebraic Approach to Abstraction in Semi-Markov Decision ...

We assume that for all s ∈ S, As is non-empty. A discrete time semi-Markov decision process (SMDP) is a ... Equivalence notions and model minimization in Markov ...

discrete-time controlled markov processes with average cost ...

Varadarajan, Markov decision processes with sample path constraints ... Serfozo, An equivalence between continuous and discrete time Markov decision processes,.

Fuel in Markov Decision Processes (FiMDP): A Practical Approach ...

Consumption Markov Decision Processes (CMDPs) are probabilistic decision ... We also transform the CMDP into the equivalent MDP with the energy constraints ...

CONSTRAINED MARKOV DECISION PROCESSES VIA ...

Our method is implemented as a reduction to any model-free on-policy bootstrap based RL algorithm, both for deterministic and stochastic policies, and discrete ...

Constrained Markov Decision Processes - 1st Edition - Routledge

This book provides a unified approach for the study of constrained Markov decision processes with a finite state space and unbounded costs.

Equivalence of Optimality Criteria for Markov Decision Process and ...

Equivalence of Optimality Criteria for Markov Decision Process and Model Predictive Control ... constrained Markov Decision Processes using MPC ... Discrete-Time ...

Linearly-solvable Markov decision problems

... discrete MDP: h (i; a) = Σj Hpij (a) log (Hpij (a)). (36). The constraints (34) are then equivalent to q (i). Σj baj (i) log (pij) = H`(i; a) h (i; a). (37).

Markov decision processes: dynamic programming and applications

Then, the constraint is equivalent to the following constraint on the ... The value of the constrained Markov decision problem with long run time average.

MARKOV DECISION PROCESSES LODEWIJK KALLENBERG ...

... Equivalence between n-discount and n-average optimality ... time returns on a single processor . . . . . . . . . . . . . 359. 8.5.2 Optimality of the µc ...

Conditions for the Solvability of the Linear Programming Formulation ...

We consider a discrete-time constrained discounted Markov decision process (MDP) with Borel state and action spaces, compact action sets, and lower semi ...

Algorithm for Constrained Markov Decision Process with Linear ...

The finite-time error bound of the pro- posed approach is provided. Despite the chal- lenge of the nonconcave objective subject to non- concave constraints, the ...

On discrete-time semi-Markov processes

We present a class of discrete-time semi-Markov chains which can be constructed as time-changed Markov chains and we obtain the related governing convolution ...

A primer on partially observable Markov decision processes ...

Solving an MDP problem means finding the best decision to implement in a given state at each time step. These decision rules are called an MDP ...

Non-Stationary Markov Decision Processes, a Worst-Case ...

We study Markov Decision Processes (MDPs) evolving over time and consider Model-Based Reinforcement Learning algorithms in this setting. We make two hypotheses: ...

Algorithms for optimization and stabilization of controlled Markov ...

model ( 1 ) is known as a controlled Markov chain, or Markov decision process (MDP)• ... Discrete-time controlled Markov processes with average cost criterion: a ...

Constrained Markov Decision Processes - Eitan Altman

... time horizon and in the discount factor. Finally, several state ... equivalent established exists an optimal expected average cost ...

Twice regularized MDPs and the equivalence between robustness ...

... constrained uncertainty sets. Both works rely on the specific structure ... Markov decision processes: discrete stochastic dynamic programming. John.

Is there MDPs (Markov Decision Process) which have a non ...

If we model a game which has no pure Nash Equilibrium and only a mixed Nash Equilibrium, the policy which optimize the long time reward can not ...

Constrained Markov Decision Processes

I The task can impose aditional constraints (time, for example). Page ... Using the discounted cost, an CMDP can be shown to be equivalent to.