Biasing the transition of Bayesian optimization algorithm between Markov chain states in dynamic environments.
Marjan KaediNasser Ghasem-AghaeeChang Wook AhnPublished in: Inf. Sci. (2016)
Keyphrases
- optimization algorithm
- dynamic environments
- markov chain
- state transition
- transition probabilities
- transition matrix
- steady state
- multi objective
- state space
- finite state
- optimization method
- markov chain monte carlo
- monte carlo method
- monte carlo
- random walk
- autonomous agents
- markov process
- differential evolution
- markov model
- particle swarm optimization pso
- mobile robot
- evolutionary multi objective
- monte carlo simulation
- bayesian networks
- bayesian learning
- hybrid optimization algorithm
- stationary distribution
- artificial bee colony
- changing environment
- bayesian inference
- posterior distribution
- state variables
- maximum likelihood
- evolutionary algorithm