The influence of memory on indoor environment exploration: A numerical study

Understanding human behavior in the context of exploration and navigation is an important but challenging problem. Such understanding can help in the design of safe structures and spaces that implicitly aid humans during evacuation or other emergency situations. In particular, the role that memory plays in this process is something that is crucial to understand. In this paper, we develop a novel serious game-based experimental approach to understanding the non-randomness and the impact of memory on the human exploration process. We show that a simple memory model, with a depth of between 6 and 8 steps, is sufficient to approximate a ‘human-like’ level of exploration efficiency. We also demonstrate the advantages that a game-based experimental methodology brings to these kinds of experiments in the amount of data that can be collected as compared to traditional experiments. We feel that these findings have important implications for ‘safety-by-design’ in complex infrastructural structures.

[1]  Zhi Li,et al.  Controlled interaction: Strategies for using virtual reality to study perception , 2010, Behavior research methods.

[2]  Barbara Hayes-Roth,et al.  Differences in spatial knowledge acquired from maps and navigation , 1982, Cognitive Psychology.

[3]  Emanuel Donchin,et al.  Video games as research tools: The Space Fortress game , 1995 .

[4]  B. Kuipers Modelling spatial knowledge , 1977, IJCAI 1977.

[5]  Louisa Dahmani,et al.  Wayfinding: The effects of large displays and 3-D perception , 2011, Behavior Research Methods.

[6]  B. Stankiewicz,et al.  Acquisition of structural versus object landmark knowledge. , 2007, Journal of experimental psychology. Human perception and performance.

[7]  Jerry Weisman,et al.  Evaluating Architectural Legibility , 1981 .

[8]  Norman I. Badler,et al.  Being a part of the crowd: towards validating VR crowds using presence , 2008, AAMAS.

[9]  James P. Crutchfield,et al.  Bayesian Structural Inference for Hidden Processes , 2013, Physical review. E, Statistical, nonlinear, and soft matter physics.

[10]  Michael O'Neill Effects of familiarity and plan complexity on wayfinding in simulated buildings , 1992 .

[11]  L Hamayon,et al.  Direction - Finding in Large Buildings , 1969 .

[12]  D. Washburn The games psychologists play (and the data they provide) , 2003, Behavior research methods, instruments, & computers : a journal of the Psychonomic Society, Inc.

[13]  E. Tolman Cognitive maps in rats and men. , 1948, Psychological review.

[14]  J. Loomis,et al.  Immersive virtual environment technology as a basic research tool in psychology , 1999, Behavior research methods, instruments, & computers : a journal of the Psychonomic Society, Inc.

[15]  R. Klatzky,et al.  Navigator: A psychologically based model of environmental learning through navigation , 1989 .

[16]  H. Akaike,et al.  Information Theory and an Extension of the Maximum Likelihood Principle , 1973 .

[17]  G. Schwarz Estimating the Dimension of a Model , 1978 .

[18]  Denis Helic,et al.  Detecting Memory and Structure in Human Navigation Patterns Using Markov Chain Models of Varying Order , 2014, PloS one.

[19]  A. Siegel,et al.  The development of spatial representations of large-scale environments. , 1975, Advances in child development and behavior.

[20]  Shannon Dawn Moeser Cognitive Mapping in a Complex Building , 1988 .

[21]  Jonathan B Freeman,et al.  MouseTracker: Software for studying real-time mental processing using a computer mouse-tracking method , 2010, Behavior research methods.

[22]  David R. Michael,et al.  Serious Games: Games That Educate, Train, and Inform , 2005 .

[23]  G. A. Miller THE PSYCHOLOGICAL REVIEW THE MAGICAL NUMBER SEVEN, PLUS OR MINUS TWO: SOME LIMITS ON OUR CAPACITY FOR PROCESSING INFORMATION 1 , 1956 .

[24]  Nikolai W F Bode,et al.  Human responses to multiple sources of directional information in virtual crowd evacuations , 2014, Journal of The Royal Society Interface.

[25]  Michael I. Posner,et al.  Computerized games to study the development of attention in childhood , 2000, Behavior research methods, instruments, & computers : a journal of the Psychonomic Society, Inc.

[26]  Benjamin Kuipers,et al.  Modeling Spatial Knowledge , 1978, IJCAI.

[27]  G W Evans,et al.  Cognitive mapping: knowledge of real-world distance and location information. , 1980, Journal of experimental psychology. Human learning and memory.

[28]  David Waller,et al.  The HIVE: A huge immersive virtual environment for research in spatial cognition , 2007, Behavior research methods.

[29]  David Gibson,et al.  The Wayfinding Handbook: Information Design for Public Places , 2009 .

[30]  C. Holahan Cognition and Environment: Functioning in an Uncertain World. , 1984 .

[31]  Dimitris Kugiumtzis,et al.  Markov chain order estimation with conditional mutual information , 2013 .

[32]  Gordon E Legge,et al.  Lost in virtual space: studies in human and ideal spatial navigation. , 2006, Journal of experimental psychology. Human perception and performance.

[33]  Donald A. Hantula,et al.  Microworlds for experimental research: Having your (control and collection) cake, and realism too , 1998 .

[34]  Mary Hegarty,et al.  Spatial Memory of Real Environments, Virtual Environments, and Maps , 2004 .

[35]  Michael Lees,et al.  An Information Processing Based Model of Pre-evacuation Behavior for Agent Based Egress Simulation , 2014 .

[36]  James M. Boyle,et al.  A systematic literature review of empirical evidence on computer games and serious games , 2012, Comput. Educ..

[37]  Doug A. Bowman,et al.  Virtual Reality: How Much Immersion Is Enough? , 2007, Computer.

[38]  Jack M. Loomis,et al.  Place learning in humans: The role of distance and direction information , 2001, Spatial Cogn. Comput..

[39]  Kevin Lynch,et al.  The Image of the City , 1960 .

[40]  Heinrich H. Bülthoff,et al.  Working Memory in Wayfinding - A Dual Task Experiment in a Virtual City , 2008, Cogn. Sci..

[41]  Nikolai W. F. Bode,et al.  Human exit route choice in virtual crowd evacuations , 2013, Animal Behaviour.

[42]  Abe Fettig,et al.  Twisted Network Programming Essentials , 2005 .

[43]  D. R. Montello,et al.  Spatial knowledge acquisition from direct experience in the environment: Individual differences in the development of metric knowledge and the integration of separately learned places , 2006, Cognitive Psychology.

[44]  Kyumin Lee,et al.  Exploring Millions of Footprints in Location Sharing Services , 2011, ICWSM.

[45]  W. McGaghie,et al.  Simulation technology for health care professional skills training and assessment. , 1999, JAMA.

[46]  Eduardo Salas,et al.  Flight Simulator Training Effectiveness: A Meta-Analysis , 1992 .

[47]  Scott D. Brown,et al.  Gamelike features might not improve data , 2013, Behavior research methods.

[48]  Michael J. Spivey,et al.  Continuous attraction toward phonological competitors. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[49]  Dimitris Kugiumtzis,et al.  Markov Chain Order estimation with Conditional Mutual Information , 2013, ArXiv.

[50]  Margaret Wilson,et al.  Six views of embodied cognition , 2002, Psychonomic bulletin & review.

[51]  Christoph Hölscher,et al.  Map Use and Wayfinding Strategies in a Multi-building Ensemble , 2006, Spatial Cognition.

[52]  Brian J. Stankiewicz,et al.  Lost in Virtual Space II: The Role of Proprioception and Discrete Actions when Navigating with Uncertainty , 2006 .

[53]  B. Kuipers,et al.  The Skeleton In The Cognitive Map , 2003 .

[54]  Michael Lees,et al.  Validation of Agent-Based Simulation through Human Computation: An Example of Crowd Simulation , 2011, MABS.

[55]  T. Gärling,et al.  Orientation in buildings: effects of familiarity, visual access, and orientation aids. , 1983, The Journal of applied psychology.

[56]  Brady T. West,et al.  Working Memory, Cues, and Wayfinding in Older Women , 2009 .

[57]  Peter M. A. Sloot,et al.  Quantitative comparison between crowd models for evacuation planning and evaluation , 2014, ArXiv.