Jul 2026· Science China Information Sciences· Vol 69· 0 citations· 47 references
TL;DR
The adaptive coordination strategy is proposed, combining coordination and tolerance to enhance adaptability and stability and outperforms classic memory-1 strategies and achieves optimal outcomes, providing a framework for understanding complex history-based behaviors beyond traditional memory-n models.
Abstract
Decision-making in natural and artificial systems is often shaped by past interactions, as individuals adjust their behavior accordingly. A persistent challenge lies in identifying successful strategies and understanding how memory influences their performance, especially when individuals’ optimal actions conflict with collective outcomes. Most theoretical studies in evolutionary dynamics have focused on memory-1 strategies, and recent studies indicate that extending memory can improve strategies’ performance. Among these, all-or-none (AoNK) strategies perform well at short memory. Our analysis reveals, however, that their effectiveness deteriorates as memory extends, showing the inherent limitations of sole coordination. Building on this, we propose the adaptive coordination strategy, combining coordination and tolerance to enhance adaptability and stability. Our theoretical analysis precisely characterizes its behavior and key properties. This strategy outperforms classic memory-1 strategies and achieves optimal outcomes, providing a framework for understanding complex history-based behaviors beyond traditional memory-n models.
This work comprehensively investigates the concept of constant-memory strategies in stochastic games, and uncovers the connection between decision models in single-agent and multi-agent contexts.
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Mechanistic analyses show that a moderate neighborhood size enables individuals to strike an optimal balance between information sufficiency and decision-making tractability, which allows them to detect reciprocal opportunities while avoiding the deterioration of decision quality due to information overload.
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