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Poster Session B: Wednesday, August 13, 1:00 – 4:00 pm, de Brug & E‑Hall

Adaptive planning and policy mixture explain the naturalistic foraging in 3D virtual reality.

Jae Young Jeon¹, Won Mok Shim², Sung Bum Michael Yoo; ¹Sung Kyun Kwan University, ²SungKyunKwan University (SKKU)

Presenter: Jae Young Jeon

Animals and humans often reject immediate rewards by using mental models to plan for future outcomes. However, proactive rejection—intentionally skipping favorable immediate options—has been understudied due to difficulties distinguishing it from forced or reactive rejections. Using a custom-designed Minecraft-based 3D foraging task paired with a sequential Bayesian inference model, we systematically identified and characterized proactive rejection behaviors. Participants strategically increased rejection of immediate rewards as spatial regularity became more apparent, resulting in enhanced overall foraging outcomes. Our computational modeling revealed that planning depth and preference for information gathering significantly predicted rejection frequency. Crucially, proactive rejection behaviors—unlike reactive rejections—were best explained by adaptive modulation of planning depth and information prioritization based on participants' confidence in spatial regularity. These findings provide mechanistic insights into proactive rejection, highlighting its potential as a behavioral marker for goal-directed planning processes.

Topic Area: Predictive Processing & Cognitive Control

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