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The Complexity of Optimizing Atomic Congestion

AAAI 2024 · Learning theory and algorithms › Submodular and game algorithms · approach: Correlated equilibria in sequential games · 1 citations (OpenAlex)

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Studies the parameterized complexity of computing system-optimal flow assignments in atomic congestion games (SOAC) and its min-max variant (mSOAC), giving NP-hardness, W[1]-hardness, and an FPT algorithm parameterized by slim treecut width plus maximum capacity.

Problem

Computing a system-optimal set of strategies (minimum total cost routing) in atomic congestion games, and its min-max variant where up to alpha agents may be left unrouted; the goal is to identify structural parameters giving tractability.

Approach

Shows that vertex-separator parameters (treewidth, treedepth) do not yield tractability and that edge-cut based parameters are the right ones; gives a dynamic program over spanning-tree decompositions (slim treecut width, local feedback edge number) with snapshot records parameterized by maximum link capacity.

Key results

Surprising findings

Limitations

Experimental setup

Builds on: Rosenthal congestion games treecut width slim treecut width spanning tree decompositions

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