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Related Questions
- How does the acquisition function handle concept drift in dynamic environments?
- Can you explain the concept of Bayesian optimization and its relevance to adapting to changing objective functions?
- What are some strategies for updating the acquisition function when new data becomes available or problem constraints change?
- How does the acquisition function balance exploration and exploitation when the objective function is changing?
- Can you discuss the importance of exploration-exploitation trade-off in dynamic optimization problems?
- What techniques can be used to adapt the acquisition function to handle changing problem constraints, such as new objective functions or constraints?
- Is there a relationship between the acquisition function and the concept of active learning, and how can it be applied to adapting to changing objective functions?
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