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20 Feb 2018: kA(a,a′). The. policy is optimised using an algorithm called GP-SARSA [7, 45] in which theQ-function is updated by calculating the posterior given the collected belief-action pairs ... The summary action kernel is defined as:. kA(a,a′) = δa(a. ′)

20 Feb 2018: Zhang and Chaudhuri2015] Chicheng Zhang and Ka-malika Chaudhuri. 2015. Active learning fromweak and strong labelers.

20 Feb 2018: 211. 2121. 1. aannna. annnnn. ka. rd (13). Here nr specifies the number of events that occurred r times and a fixed discounting factor was used if they are zero.

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20 Feb 2018: Q(b,a) GP (0,k((b,a), (b,a))) (2). where the kernel k(, ) is factored into separate kernels overbelief and action spaces kB(b,b′)kA(a,a′). ... kA(a,a′) = δa(a. ′) (7). where δa(a′) = 1 iff a = a′, 0 otherwise.

20 Feb 2018: kA(a,a′). For a training sequence of belief state-action pairs B = [(b0,a0),. , ... kA(a,a′) = δa(a. ′) (6). where δa(a′) = 1 iff a = a′, 0 otherwise.

20 Feb 2018: and action spaces kB(b,b′)kA(a,a′). ... kA(a,a′) = δa(a. ′) (5). where δa(a′) = 1 iff a = a′, 0 otherwise.

20 Feb 2018: and action spaces kB(b,b′)kA(a,a′). ... kA(a,a′) = δa(a. ′) (5). where δa(a′) = 1 iff a = a′, 0 otherwise.

20 Feb 2018: kA(a,a′) = δa(a. ′), (7). where δa(a′) = 1 iff a = a′, 0 otherwise.4.2. ... The kernelfunction between two sets of actions is. kA(aB,aE) = δaB(a.

20 Feb 2018: Q(b,a) GP (0,k((b,a), (b,a))). (41). The kernel k(, ) is often factored into separate kernels over the belief state and actionspaces kB(b,