Do Environment-Modification Behaviors and Gamers' Immersiveness Shape Exceptionalism Beliefs?
- URL: http://arxiv.org/abs/2511.17591v1
- Date: Mon, 17 Nov 2025 05:19:11 GMT
- Title: Do Environment-Modification Behaviors and Gamers' Immersiveness Shape Exceptionalism Beliefs?
- Authors: Quan-Hoang Vuong, Fatemeh Kianfar, Thi Mai Anh Tran, Ni Putu Wulan Purnama Sari, Cresensia Dina Candra Kumaladewi, Viet-Phuong La, Minh-Hoang Nguyen,
- Abstract summary: Human exceptionalism strongly shapes human-nature perceptions, thinking, values, and behaviors.<n>This study investigates how virtual environment-modification behaviors and players' sense of immersiveness jointly shape exceptionalism.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Human exceptionalism strongly shapes human-nature perceptions, thinking, values, and behaviors. Yet little is known about how virtual ecological environments influence this mindset. As digital worlds become increasingly immersive and ecologically sophisticated, they provide novel contexts for examining how human value systems are formed and transformed. This study investigates how virtual environment-modification behaviors and players' sense of immersiveness jointly shape exceptionalism, drawing on worldviews from quantum mechanics and mathematical logic. Using Granular Interaction Thinking Theory (GITT) and the Bayesian Mindsponge Framework (BMF analytics), we analyze five key activities--tree planting, flower planting, flower crossbreeding, terraforming, and creating conditions for bug respawn--based on a multinational dataset of 640 Animal Crossing: New Horizons players from 29 countries. Results reveal two behavioral clusters distinguished by controllability. High-controllability behaviors (i.e., flower planting and terraforming) predict higher exceptionalism, whereas the flower-planting effect reverses among highly immersed players. Low-controllability behaviors (i.e., flower crossbreeding and manipulating bug spawning) predict lower exceptionalism, but these associations weaken or reverse under high immersiveness, respectively. These findings offer insights into leveraging virtual worlds to cultivate Nature Quotient (NQ), mitigate exceptionalist tendencies, and foster eco-surplus cultural orientations.
Related papers
- Learning Situated Awareness in the Real World [63.75211123289058]
SAW-Bench is a novel benchmark for evaluating egocentric situated awareness using real-world videos.<n>It probes a model's observer-centric understanding with six different awareness tasks.<n>Our comprehensive evaluation reveals a human-model performance gap of 37.66%, even with the best-performing MFM, Gemini 3 Flash.
arXiv Detail & Related papers (2026-02-18T18:22:52Z) - WorldLens: Full-Spectrum Evaluations of Driving World Models in Real World [100.68103378427567]
Generative world models are reshaping embodied AI, enabling agents to synthesize realistic 4D driving environments that look convincing but often fail physically or behaviorally.<n>We introduce WorldLens, a full-spectrum benchmark evaluating how well a model builds, understands, and behaves within its generated world.<n>We further construct WorldLens-26K, a large-scale dataset of human-annotated videos with numerical scores and textual rationales, and develop WorldLens-Agent.
arXiv Detail & Related papers (2025-12-11T18:59:58Z) - How Immersiveness Shapes the Link Between Anthropocentric Values and Resource Exploitation in Virtual Worlds [0.0]
This study investigates how anthropocentric values are associated with resource-exploiting behaviors in virtual ecosystems.<n>Using data from 640 Animal Crossi,g: New Horizons players across 29 countries, the study reveals complex links between anthropocentric worldviews and in-game behaviors.
arXiv Detail & Related papers (2025-11-26T09:45:20Z) - The Emergence of Complex Behavior in Large-Scale Ecological Environments [33.8561801938052]
We explore how physical scale and population size shape the emergence of complex behaviors in open-ended ecological environments.<n>Our goal is not to optimize a single high-performance policy, but instead to examine how behaviors emerge and evolve across large populations.
arXiv Detail & Related papers (2025-10-21T02:03:25Z) - DeceptionBench: A Comprehensive Benchmark for AI Deception Behaviors in Real-world Scenarios [57.327907850766785]
characterization of deception across realistic real-world scenarios remains underexplored.<n>We establish DeceptionBench, the first benchmark that systematically evaluates how deceptive tendencies manifest across different domains.<n>On the intrinsic dimension, we explore whether models exhibit self-interested egoistic tendencies or sycophantic behaviors that prioritize user appeasement.<n>We incorporate sustained multi-turn interaction loops to construct a more realistic simulation of real-world feedback dynamics.
arXiv Detail & Related papers (2025-10-17T10:14:26Z) - Avoiding Death through Fear Intrinsic Conditioning [48.07595141865156]
We introduce an intrinsic reward function inspired by early amygdala development and produce this intrinsic reward through a novel memory-augmented neural network architecture.<n>We show how this intrinsic motivation serves to deter exploration of terminal states and results in avoidance behavior similar to fear conditioning observed in animals.
arXiv Detail & Related papers (2025-06-05T19:24:51Z) - Imagine, Verify, Execute: Memory-guided Agentic Exploration with Vision-Language Models [81.08295968057453]
We present IVE, an agentic exploration framework inspired by human curiosity.<n>We evaluate IVE in both simulated and real-world tabletop environments.
arXiv Detail & Related papers (2025-05-12T17:59:11Z) - The Introspective Agent: Interdependence of Strategy, Physiology, and
Sensing for Embodied Agents [51.94554095091305]
We argue for an introspective agent, which considers its own abilities in the context of its environment.
Just as in nature, we hope to reframe strategy as one tool, among many, to succeed in an environment.
arXiv Detail & Related papers (2022-01-02T20:14:01Z) - Causal Curiosity: RL Agents Discovering Self-supervised Experiments for
Causal Representation Learning [24.163616087447874]
We introduce em causal curiosity, a novel intrinsic reward.
We show that it allows our agents to learn optimal sequences of actions.
We also show that the knowledge of causal factor representations aids zero-shot learning for more complex tasks.
arXiv Detail & Related papers (2020-10-07T02:07:51Z) - On the environment-destructive probabilistic trends: a perceptual and
behavioral study on video game players [0.0]
This study uses Animal Crossing: New Horizons as a unique case study of how video games can affect humans' environmental perceptions.
A dataset of 584 observations from a survey of ACNH players has enabled us to explore the relationship between in-game behaviors and perceptions.
arXiv Detail & Related papers (2020-06-17T08:05:40Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.