Human Explore-Exploit Behavior in Changing Environments, Experimental Data

Experimental data from an 'observe or bet' task comparing human behavior in changing versus unchanging environments. The dataset likely contains trial-level records from a behavioral experiment conducted by Danielle Navarro at The University of Texas at Austin. A Bayesian analysis of the task is presented, with findings suggesting human judgments align with a model assuming a higher-than-actual rate of environmental change.

Use Cases

• Modeling human explore-exploit strategies based on the described 'observe or bet' task paradigm.
• Comparing Bayesian model predictions to empirical choice data from changing and unchanging environments.
• Investigating asymmetric consequences in decision-making based on the described tendency to overestimate change rates.

Strengths

• Data originates from a controlled behavioral experiment with a defined 'observe or bet' task.
• Analysis includes a formal Bayesian model for the task, providing a theoretical framework.
• Dataset is associated with peer-reviewed research published on paperswithcode.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Last update date is unknown; freshness unverified.

Provenance

Source

Danielle Navarro, The University of Texas at Austin

Collection Method

Behavioral experiment ('observe or bet' task) with human participants.