Abstract
Incentive contracts with multiple agents is a classical decentralized decision-making problem with asymmetric information. Contract design aims to incentivize noncooperative agents to act in the principal's interest over a planning horizon. We extend the single-agent incentive contract to a multiagent setting with history-dependent terminal conditions. Our contributions include: (a) Finding sufficient conditions for the existence of optimal multiagent incentive contracts and conditions under which they form a unique Nash Equilibrium; (b) Showing that the optimal multiagent incentive contracts can be solved by a Hamilton-Jacobi-Bellman (HJB) equation with equilibrium constraints; (c) Proposing a backward iterative algorithm to solve the problem.
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