Coordination in dynamic domains involves balancing predictability and responsiveness: agents must be predictable enough to anticipate and plan future interactions while being responsive enough to react to unexpected situations. The partial global planning approach to coordination provides a framework for flexibly balancing these opposing needs. In this approach, agents communicate about their current local plans to build up partial global plans (PGPs) that specify cooperative actions and interactions. When their plans change, agents must decide whether the time and effort of reformulating their PGPs is worthwhile, or whether working predictably with slightly out-of-date PGPs is more cost effective. In this paper, we briefly outline the partial global planning approach, discuss how it flexibly balances predictability and responsiveness, and experimentally show how different balances affect behavior in a simulated problem-solving network.
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