Human Exploration in Complex Problem-Solving Tasks: More Effortful Interaction Leads to Higher Efficiency
preprint
OA: closed
CC-BY-4.0
AI-generated summary
This study investigated human interaction in complex problem-solving tasks and found that greater effortful interaction correlates with increased efficiency.
One-sentence paraphrase of the abstract; not a substitute for reading it. No clinical advice. How this works
Abstract
Exploration, a cornerstone of the human ability to solve novel problems, is a complex process. Most studies on human exploration used overly simple tasks that isolate variables but poorly reflect problems humans evolved to solve–limiting the generalizability of the results. To address this limitation, we introduce the Lockbox paradigm, a novel, ecologically valid, and challenging task that requires active exploration and physical interaction.Data from 263 participants interacting with the Lockbox across three different interaction modalities of varying interaction costs, reveal a remarkable ability to adapt and solve problems efficiently in complex scenarios. By comparing the interaction modalities, we demonstrate the critical role of cost variations, such as physical and temporal costs, in driving attentiveness and shaping exploration strategies. These findings provide important insights into human exploration strategies, with potential applications in fields such as robotics and artificial intelligence.
My notes (saved in your browser only)
Citation neighborhood (no data yet)
We don't have any in-corpus citations linked to this paper yet. This is a recent paper (2025) — citers typically take a year or two to land, and the OpenAlex reference graph may still be filling in.
Source provenance
- europepmc
- last seen: 2026-05-20T01:45:00.602351+00:00
- unpaywall
- last seen: 2026-05-26T02:00:01.498150+00:00
License: CC-BY-4.0