Bayesian Adaptive Estimation with Theoretical Bound: An Exploration-Exploitation Approach

Algorithm 1

Exploration-exploitation Bayesian adaptive estimation (EE-BAE).

	Input: parameter space , initial parameter prior , stimulus space , threshold , experiment trial .
	Output: estimated parameter .
	Step 1: Set .
	Step 2: For all , compute by (1). Compute binary posterior entropy and binary conditional posterior entropy by equations (5) and (7). Calculate mutual information .
	Step 3: Select and compute parameter entropy . Apply the stimulus to the subject and observe the subject’s response . Update the parameter prior distribution , and then let . If ; go to Step 2. Else, go to Step 4.
	Step 4: Select randomly. Apply the stimulus to the subject and observe the subject’s response . Update the parameter prior distribution . If , let and go back to Step 4. Else, output the parameter estimator .
	End