An affordance-based formalism for modeling human-involvement in complex systems for prospective control

We propose a predictive modeling framework for human-involved complex systems in which humans play controlling roles. Affordance theory provides definitions of human actions and their associated properties, and the affordance-based Finite State Automata (FSA) model is capable of mapping the nondeterministic human actions into computable components in modeling formalism. In this paper, we further investigate the role of perception in human actions and examine the representation of perceptual elements in affordance-based modeling formalism. We also propose necessary and sufficient conditions for mapping perception-based human actions into systems theory to develop a predictive modeling formalism in the context of prospective control. A driving example is used to show how to build a formal model of human-involved complex system for prospective control. The suggested modeling frameworks will increase the soundness and completeness of a modeling formalism as well as can be used as guide to model human activities in a complex system.

[1]  Alex Kirlik,et al.  Supervisory control in a dynamic and uncertain environment: a process model of skilled human-environment interaction , 1993, IEEE Trans. Syst. Man Cybern..

[2]  J. Gibson The Ecological Approach to Visual Perception , 1979 .

[3]  Affordance-based Computational Model of Driver Behavior on Highways : A Colored Petri Net Approach , .

[4]  P Haggard,et al.  The psychology of action. , 2001, British journal of psychology.

[5]  J. Yolton Reasons for Realism. Selected Essays of James J. Gibson. Edited by EDWARD REED and REBECCA JONES. New Jersey: Lawrence Erlbaum Associates, 1982. Pp. xvi + 449. $39.95 , 1984 .

[6]  Brett R Fajen,et al.  Perceiving Possibilities for Action: On the Necessity of Calibration and Perceptual Learning for the Visual Guidance of Action , 2005, Perception.

[7]  Namhun Kim,et al.  Using finite state automata (FSA) for formal modelling of affordances in human-machine cooperative manufacturing systems , 2010 .

[8]  M. Turvey Affordances and Prospective Control: An Outline of the Ontology , 1992 .

[9]  T. Stoffregen Affordances as Properties of the Animal-Environment System , 2003, How Shall Affordances be Refined? Four Perspectives.

[10]  Ronald C. Arkin,et al.  An Behavior-based Robotics , 1998 .

[11]  S. Greenberg,et al.  The Psychology of Everyday Things , 2012 .

[12]  Ling Rothrock,et al.  Affordance-based computational model of driver behavior on highway systems: A Colored Petri Net approach , 2007, 2007 IEEE International Conference on Systems, Man and Cybernetics.

[13]  Herbert A. Simon,et al.  The Sciences of the Artificial , 1970 .

[14]  Robert E. Shaw,et al.  The Agent-Environment Interface: Simon's Indirect or Gibson's Direct Coupling? , 2003 .

[15]  J. Gibson The Senses Considered As Perceptual Systems , 1967 .

[16]  Thomas B. Sheridan,et al.  Function allocation: algorithm, alchemy or apostasy? , 2000, Int. J. Hum. Comput. Stud..

[17]  Peter Pirolli,et al.  Information Foraging , 2009, Encyclopedia of Database Systems.

[18]  E. Reed,et al.  Reasons For Realism: Selected Essays Of James J. Gibson , 1982 .

[19]  H. Simon,et al.  The sciences of the artificial (3rd ed.) , 1996 .

[20]  S S Stevens,et al.  HUMAN ENGINEERING FOR AN EFFECTIVE AIR-NAVIGATION AND TRAFFIC-CONTROL SYSTEM, AND APPENDIXES 1 THRU 3 , 1951 .

[21]  Keith S. Jones,et al.  What Is an Affordance? , 2003, How Shall Affordances be Refined? Four Perspectives.

[22]  Michael W. Levine Levine & Shefner's fundamentals of sensation and perception , 2000 .