- Near Optimal Exploration|Exploitation in Non|Communicating ...🔍
- Reduction of total|cost and average|cost MDPs with weakly ...🔍
- Logarithmic regret in communicating MDPs🔍
- Convergence and Near Optimality via Quantization under Weak ...🔍
- Learning in Online MDPs🔍
- Communicating MDPs🔍
- Reinforcement Learning for Weakly|Coupled MDPs and an ...🔍
- Linear Program for Communicating MDPs with Multiple Constraints🔍
weakly| communicating mdps
Near Optimal Exploration-Exploitation in Non-Communicating ...
Authors. Ronan Fruit, Matteo Pirotta, Alessandro Lazaric. Abstract. While designing the state space of an MDP, it is common to include states that are ...
Reduction of total-cost and average-cost MDPs with weakly ...
This paper describes conditions under which undiscounted MDPs with infinite state spaces and weakly continuous transition kernels can be transformed into ...
Logarithmic regret in communicating MDPs: Leveraging known ...
Abstract. We study regret minimization in an average-reward and communicating Markov Decision. Process (MDP) with known dynamics, but unknown reward ...
REGAL: a regularization based algorithm for reinforcement learning ...
We provide an algorithm that achieves the optimal regret rate in an unknown weakly communicating Markov Decision Process (MDP).
Convergence and Near Optimality via Quantization under Weak ...
Abstract. Reinforcement learning algorithms often require finiteness of state and action spaces in Markov decision processes (MDPs) (also called controlled ...
(PDF) REGAL: A Regularization based Algorithm for Reinforcement ...
PDF | We provide an algorithm that achieves the optimal regret rate in an unknown weakly communicating Markov Decision Process (MDP).
Logarithmic regret in communicating MDPs: Leveraging known ...
We study regret minimization in an average-reward and communicating Markov Decision Process (MDP) with known dynamics, but unknown reward function.
Learning in Online MDPs: Is there a Price for Handling the ...
in communicating MDPs with full information. Thus, we show that having communicating structure alone does not add any statistical price (see Table 1). 1.1 ...
Communicating MDPs: Equivalence and LP properties - UQ eSpace
The University of Queensland's institutional repository, UQ eSpace, aims to create global visibility and accessibility of UQ's scholarly research.
Reinforcement Learning for Weakly-Coupled MDPs and an ...
Reinforcement Learning for Weakly-Coupled MDPs and an Application to Planetary Rover Control Weakly-coupled Markov decision processes can be ...
Linear Program for Communicating MDPs with Multiple Constraints
The mapping is used not only to prove that the unichain linear program solves the average reward communicating MDPs with multiple constraints on average ...
[PDF] REGAL: A Regularization based Algorithm for Reinforcement ...
An algorithm is provided that achieves the optimal regret rate in an unknown weakly communicating Markov Decision Process (MDP) where, in each episode, ...
Communicating MDPs: Equivalence and LP properties
Filar, Jerzy ; Schultz, Todd. / Communicating MDPs: Equivalence and LP properties. In: Operations Research Letters. 1988 ; Vol. 7, No. 6. pp. 303-307. ... Filar, ...
Span-Based Optimal Sample Complexity for Weakly Communicating ...
We study the sample complexity of learning an $\varepsilon$-optimal policy in an average-reward Markov decision process (MDP) under a ...
Solving Very Large Weakly Coupled Markov Decision Processes
We can therefore view each task as an MDP. How- ever, these MDPs are weakly coupled by resource constraints: actions selected for one MDP restrict the ...
View of Communication-Based Decomposition Mechanisms for ...
... weakly coupled MDPs by Bererton et al. (2003).In this paper, the solution to this type of more complex decentralized problems includestemporally abstracted ...
Solving Very Large Weakly Coupled Markov Decision Processes
We can therefore view each task as an MDP. How- ever, these MDPs are weakly coupled by resource constraints: actions selected for one MDP restrict the ...
Approximate dynamic programming for weakly coupled Markov ...
The research objective of this dissertation is to build Markov decision process (MDP) models of four classes of dynamic resource allocation problems under ...
REGAL : a regularization based algorithm for reinforcement learning ...
Thus, we have proved the result for all weakly communicating MDPs. We can now derive the fact that sp(h⋆ ) ≤ Dow . Corollary 5. For any weakly communicating MDP ...
Learning and Planning in Average-Reward Markov Decision ...
While our theory was developed for communicating MDPs, it can be extended with some modification to the more general weakly communicating MDP case (see the ...