Distributed decision-making over mobile adaptive networks

Decentralized Decision-Making Over Multi-Task Networks

“…update Y k i according to (13) find Q k,i and C k (i) update p k (i) according to (17) if p k (i) = 1 then switch w k,i−1 according to (18) resend w k,i−1 end if for ℓ ∈ N k do update {h ℓk (i)} according to (19) update {g ℓk (i)} according to (20) update {ȧ ℓk (i)} according to ( receives the anchor vector directly from agent m. If not, i.e., m / ∈ N k , then agent k depends on another agent ℓ ∈ N k that has already a copy of ψ m,i .…”

“…Figure 11 shows the statistical profile of the regressors and noise across the agents. Every agent k updates its location according to the motion mechanism described in [19]. Figure 12 shows the maneuver of the agents over time where the models (sources) are represented by squares.…”

“…In the latter case, agents need to decide between the multiple objectives and reach agreement on following a single objective for the entire network. In the earlier works [18,19], a scenario was considered where agents were assumed to sense data arising from two models, and a diffusion strategy was developed to enable all agents to agree on estimating a single model. The algorithm developed in [18] relied on binary labeling and is applicable only to situations involving two models.…”

“…Learning the desired models of the neighbors after the switching step. This step is performed by building the matrix H i in step (19) in Section IV. The information provided by each entry h ℓk (i) is whether the corresponding agents ℓ and k have the same desired model or not after the switching step.…”

“…update Y k i according to (13) find Q k,i and C k (i) update p k (i) according to (17) if p k (i) = 1 then switch w k,i−1 according to (18) resend w k,i−1 end if for ℓ ∈ N k do update {h ℓk (i)} according to (19) update {g ℓk (i)} according to (20) update { ȧℓk (i)} according to (23) update {ä ℓk (i)} according to (24) end for…”