Quantum logic gate synthesis as a Markov decision process
Oct 25, 2023 · By forming discrete MDPs, we solve for the optimal policy exactly through policy iteration. We find optimal paths that correspond to the shortest possible sequence of gates to prepare a state or...
Markov Decision Process (MDP) Modelings — Quantum …
We propose three different ways to model the quantum circuit design (QCD) task within a Markov Decision Process (MDP) framework: Matrix Representation. Reverse Matrix Representation. Tensor Network (TN) Representation. In each MDP …
By forming discrete MDPs, we solve for the optimal policy exactly through policy iteration. We find optimal paths that correspond to the shortest possible sequence of gates to prepare a state or...
To address this problem, we study Markov Decision Processes (MDP) under the influence of an external temporal process. First, we formalize this notion and derive conditions under which the problem becomes tractable with suitable solutions. We propose a pol-icy iteration algorithm to solve this problem and theoretically analyze its performance.
Markov Decision Processes (MDP) and Bellman Equations
We've covered state-value functions, action-value functions, model-free RL and model-based RL. They form general overarching categories of how we design our agent. However, typically we don't know the environment entirely then there is not closed form solution in getting optimal action-value and state-value functions.
Reinforcement Learning via Markov Decision Process
Dec 1, 2020 · Learn about how to use reinforcement learning via the Markov Decision Process (MDP) along with an easy to understand example.
Guide to Markov Decision Process in Machine Learning and AI
Feb 20, 2025 · The Markov Decision Process (MDP) is an important idea in machine learning and artificial intelligence, especially in reinforcement learning. It helps model decision-making when results are uncertain and partly controlled by an agent.
o An MDP is defined by: o A set of states s ∈S o A set of actions a ∈A o A transition function T(s, a, s ’) o Probability that a from s leads to s’, i.e., P(s’| s, a) o Also called the model or the dynamics o A reward function R(s, a, s ’) o Sometimes just R(s) or R(s’) 8
25 questions with answers in MDP | Science topic - ResearchGate
Dec 22, 2023 · MDP is a discrete-time stochastic control process, providing a mathematical framework for modeling decision making in situations where outcomes are partly random and partly under the control of a...
Time-Dependence in Multi-Agent MDP Applied to Gate …
Abstract: Many disturbances can impact gate assignments in daily operations of an airport. Gate Assignment Problem (GAP) is the main task of an airport to ensure smooth flight-to-Gate assignment managing all disturbances.