Information-Seeking Decision Strategies Mitigate Risk in Dynamic, Uncertain Environments
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Abstract (arXiv)
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.
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References · 5
- 2021People construct simplified mental representations to plancited by 47
- 2022Optimal policies for Bayesian olfactory search in turbulent flowscited by 4
- 2019Analyzing dynamic decision-making models using Chapman-Kolmogorov equationscited by 2
- 2015Stochastic models of evidence accumulation in changing environmentscited by 1
- 2018Optimizing sequential decisions in the drift-diffusion modelcited by 1
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