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Extra resources for A Progressive Lossless Near-Lossless Image Compression Algorithm

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This can in principle be done by splitting the search space during search and letting the agents participate in all search processes. The resulting algorithm is termed Concurrent Backtraking (ConcBT) [69]. The splitting of the search space can be done dynamically, to balance the load of computation among all agents. , ConcDB) and is the best performing DisCSP algorithm to date [74]. It is described in Chapter 7. In analogy to centralized search, algorithms can be designed so that they do not guarantee completeness.

This is done by checking if the accumulated cost of the partial assignments made so far exceeds the upper bound (line 14). 1: The Branch and Bound Algorithm Function BranchAndBound(P A, LB, U B, X, D, C): 1. if ( X = ∅ ) then return LB 2. i ← ChooseVar(X) 3. foreach a ∈ Di do 4. DD ← D ; CC ← C ; nP A ← P A + (Xi = a) ; nLB ← LB + U naryCost(a) 5. LookAhead(i, a, CC) 6. if (LocalConsist(nLB, U B, X − {i}, DD, CC)) then 7. U B ← BranchAndBound(nP A, nLB, U B, X − {i}, DD, CC) 8. return U B Procedure LookAhead(i, a, C): 9.

The reason for designing such algorithms is that they can be fast on large and hard problems [63, 66]. The common approach to incomplete search is to design search steps that perform local computaions. This fits very well the nature of distributed computation. Agents exchange messages with their neighbors, achieving agreement on their assignment in a local neighborhood, such that some objective function is minimized. , conflicts). In order to achieve locally consistent assignments, in a stable distributed process, it is necessary to synchronize each step of the algorithm across all neighborhoods in the problem.

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