信息探索策略在动态不确定环境中更稳定，风险更低。
Information-Seeking Decision Strategies Mitigate Risk in Dynamic, Uncertain Environments
- 比较了追求奖励与追求信息的决策策略
- 信息策略虽略少奖励，但结果更稳定可预测
- 适合需要降低风险的现实决策场景
在动态不确定环境中生存，个体需平衡信息获取与决策执行。现有模型多侧重优化收益或信息积累以应对未知目标，但两者优劣对比受限于理想化静态环境。本研究在动态觅食任务中比较了规范性的奖励寻求与信息寻求策略。二者随环境不确定性变化均呈现探索-利用的转换行为，但行动细节存在细微差异：奖励策略平均收益略高，而信息策略结果更一致、可预测。结果表明，信息寻求行为在几乎不损失收益的前提下，能有效降低风险，具有适应性价值。
原文摘要 · Abstract (English)
To survive in dynamic and uncertain environments, individuals must develop effective decision strategies that balance information gathering and decision commitment. Models of such strategies often prioritize either optimizing tangible payoffs, like reward rate, or gathering information to support a diversity of (possibly unknown) objectives. However, our understanding of the relative merits of these two approaches remains incomplete, in part because direct comparisons have been limited to idealized, static environments that lack the dynamic complexity of the real world. Here we compared the performance of normative reward- and information-seeking strategies in a dynamic foraging task. Both strategies show similar transitions between exploratory and exploitative behaviors as environmental uncertainty changes. However, we find subtle disparities in the actions they take, resulting in meaningful performance differences: whereas reward-seeking strategies generate slightly more reward on average, information-seeking strategies provide more consistent and predictable outcomes. Our findings support the adaptive value of information-seeking behaviors that can mitigate risk with minimal reward loss.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。