Safe Metropolis-Hastings algorithm and its application to swarm control
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Publication:1697161
DOI10.1016/j.sysconle.2017.10.006zbMath1380.93297OpenAlexW2771099899MaRDI QIDQ1697161
Behçet Açıkmeşe, Mahmoud El Chamie
Publication date: 15 February 2018
Published in: Systems \& Control Letters (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.sysconle.2017.10.006
Stochastic programming (90C15) Markov chains (discrete-time Markov processes on discrete state spaces) (60J10) Decentralized systems (93A14) Synthesis problems (93B50)
Cites Work
- What do we know about the Metropolis algorithm?
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- Fast linear iterations for distributed averaging
- Markov Chain Approach to Probabilistic Guidance for Swarms of Autonomous Agents
- Implicit dual control based on particle filtering and forward dynamic programming
- Convex Necessary and Sufficient Conditions for Density Safety Constraints in Markov Chain Synthesis
- Distributed Weight Selection in Consensus Protocols by Schatten Norm Minimization
- Fastest Mixing Markov Chain on Graphs with Symmetries
- The Markov chain Monte Carlo revolution
- Fastest Mixing Markov Chain on a Graph
- Controlled Markov chains with safety upper bound
- Stability of Model-Based Networked Control Systems With Time-Varying Transmission Times
- The Monte Carlo Method
- Monte Carlo strategies in scientific computing
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