Exploration and Skill Acquisition in a Major Online Game

Using data from a major commercial online game, Destiny, we track the development of player skill across time. From over 20,000 player record we identify 3475 players who have played on 50 or more days. Our focus is on how variability in elements of play affect subsequent skill development. After validating the persistent influence of differences in initial performance between players, we test how practice spacing, social play, play mode variability and a direct measure of game-world exploration affect learning rate. These latter two factors do not affect learning rate. Players who space their practice more learn faster, in line with our expectations, whereas players who coordinate more with other players learn slower, which contradicts our initial hypothesis. We conclude that not all forms of practice variety expedite skill acquisition. Online game telemetry is a rich domain for exploring theories of optimal skill acquisition.

[1]  T. Stafford,et al.  Tracing the Trajectory of Skill Learning With a Very Large Sample of Online Game Players , 2014, Psychological science.

[2]  K. M. Newell,et al.  Searching for solutions to the coordination function : learning as exploratory behavior , 1992 .

[3]  Diego Klabjan,et al.  Guns and guardians: Comparative cluster analysis and behavioral profiling in destiny , 2016, 2016 IEEE Conference on Computational Intelligence and Games (CIG).

[4]  C. Gallistel,et al.  The learning curve: implications of a quantitative analysis. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[5]  J. V. Rossum SCHMIDT'S SCHEMA THEORY: THE EMPIRICAL BASE OF THE VARIABILITY OF PRACTICE HYPOTHESIS , 1990 .

[6]  Allen and Rosenbloom Paul S. Newell,et al.  Mechanisms of Skill Acquisition and the Law of Practice , 1993 .

[7]  Thomas Hofmann,et al.  TrueSkill™: A Bayesian Skill Rating System , 2007 .

[8]  Tom Minka,et al.  TrueSkillTM: A Bayesian Skill Rating System , 2006, NIPS.

[9]  R. Magill,et al.  A REVIEW OF THE CONTEXTUAL INTERFERENCE EFFECT IN MOTOR SKILL ACQUISITION , 1990 .

[10]  Johanna Pirker,et al.  Integrating and Inspecting Combined Behavioral Profiling and Social Network Models in Destiny , 2016, ICEC.

[11]  Kevin Gurney,et al.  A Novel Task for the Investigation of Action Acquisition , 2012, PloS one.

[12]  Gary Lupyan,et al.  Discovering Psychological Principles by Mining Naturally Occurring Data Sets , 2016, Top. Cogn. Sci..

[13]  Richard S. Sutton,et al.  Reinforcement Learning: An Introduction , 1998, IEEE Trans. Neural Networks.

[14]  R. A. Carlson,et al.  Acquisition of intellectual and perceptual-motor skills. , 2001, Annual review of psychology.

[15]  T. Cover,et al.  A sandwich proof of the Shannon-McMillan-Breiman theorem , 1988 .

[16]  M. Khamassi,et al.  Dopaminergic Control of the Exploration-Exploitation Trade-Off via the Basal Ganglia , 2012, Front. Neurosci..

[17]  Neil Charness,et al.  The role of deliberate practice in chess expertise , 2005 .

[18]  R. Schmidt A schema theory of discrete motor skill learning. , 1975 .

[19]  Edward Vul,et al.  PSYCHOLOGICAL SCIENCE Research Article Spacing Effects in Learning A Temporal Ridgeline of Optimal Retention , 2022 .

[20]  Tamassia Marco,et al.  Predicting player churn in destiny: A Hidden Markov models approach to predicting player departure in a major online game , 2016 .

[21]  Peter P. J. L. Verkoeijen,et al.  Spacing and Testing Effects: A Deeply Critical, Lengthy, and At Times Discursive Review of the Literature , 2010 .

[22]  Ekaterina R. Stepanova,et al.  Using Video Game Telemetry Data to Research Motor Chunking, Action Latencies, and Complex Cognitive-Motor Skill Learning , 2017, Top. Cogn. Sci..

[23]  M. Blair,et al.  Video Game Telemetry as a Critical Tool in the Study of Complex Skill Learning , 2013, PloS one.

[24]  Tom Stafford,et al.  Testing Sleep Consolidation in Skill Learning: A Field Study Using an Online Game , 2017, Top. Cogn. Sci..

[25]  Rajiv Ranganathan,et al.  Motor Learning through Induced Variability at the Task Goal and Execution Redundancy Levels , 2010, Journal of motor behavior.

[26]  Wayne D. Gray,et al.  Plateaus, Dips, and Leaps: Where to Look for Inventions and Discoveries During Skilled Performance , 2017, Cogn. Sci..

[27]  Annick Lesne,et al.  Shannon entropy: a rigorous notion at the crossroads between probability, information theory, dynamical systems and statistical physics , 2014, Mathematical Structures in Computer Science.

[28]  Sara Fripp A learning curve. , 2014, Midwives.