Decision-Making under Ambiguity Is Modulated by Visual Framing, but Not by Motor vs. Non-Motor Context. Experiments and an Information-Theoretic Ambiguity Model

A number of recent studies have investigated differences in human choice behavior depending on task framing, especially comparing economic decision-making to choice behavior in equivalent sensorimotor tasks. Here we test whether decision-making under ambiguity exhibits effects of task framing in motor vs. non-motor context. In a first experiment, we designed an experience-based urn task with varying degrees of ambiguity and an equivalent motor task where subjects chose between hitting partially occluded targets. In a second experiment, we controlled for the different stimulus design in the two tasks by introducing an urn task with bar stimuli matching those in the motor task. We found ambiguity attitudes to be mainly influenced by stimulus design. In particular, we found that the same subjects tended to be ambiguity-preferring when choosing between ambiguous bar stimuli, but ambiguity-avoiding when choosing between ambiguous urn sample stimuli. In contrast, subjects’ choice pattern was not affected by changing from a target hitting task to a non-motor context when keeping the stimulus design unchanged. In both tasks subjects’ choice behavior was continuously modulated by the degree of ambiguity. We show that this modulation of behavior can be explained by an information-theoretic model of ambiguity that generalizes Bayes-optimal decision-making by combining Bayesian inference with robust decision-making under model uncertainty. Our results demonstrate the benefits of information-theoretic models of decision-making under varying degrees of ambiguity for a given context, but also demonstrate the sensitivity of ambiguity attitudes across contexts that theoretical models struggle to explain.

[1]  Evan M. Gordon,et al.  Neural Signatures of Economic Preferences for Risk and Ambiguity , 2006, Neuron.

[2]  J. Pratt RISK AVERSION IN THE SMALL AND IN THE LARGE11This research was supported by the National Science Foundation (grant NSF-G24035). Reproduction in whole or in part is permitted for any purpose of the United States Government. , 1964 .

[3]  Colin Camerer,et al.  Recent developments in modeling preferences: Uncertainty and ambiguity , 1992 .

[4]  P. Glimcher,et al.  Title: the Neural Representation of Subjective Value under Risk and Ambiguity 1 2 , 2009 .

[5]  Jordi Grau-Moya,et al.  Risk-Sensitivity in Bayesian Sensorimotor Integration , 2012, PLoS Comput. Biol..

[6]  Gideon Keren,et al.  On the robustness and possible accounts of ambiguity aversion , 1999 .

[7]  Konrad P. Körding,et al.  Bayesian Integration and Non-Linear Feedback Control in a Full-Body Motor Task , 2009, PLoS Comput. Biol..

[8]  E. Todorov Optimality principles in sensorimotor control , 2004, Nature Neuroscience.

[9]  Michael S Landy,et al.  Motor control is decision-making , 2012, Current Opinion in Neurobiology.

[10]  Kenneth J. Arrow,et al.  Studies in Resource Allocation Processes: Appendix: An optimality criterion for decision-making under ignorance , 1977 .

[11]  M. Marinacci,et al.  A Smooth Model of Decision Making Under Ambiguity , 2003 .

[12]  I. Gilboa,et al.  Advances in Economics and Econometrics: Ambiguity and the Bayesian Paradigm , 2011 .

[13]  I. Gilboa,et al.  Maxmin Expected Utility with Non-Unique Prior , 1989 .

[14]  David Schmeidleis SUBJECTIVE PROBABILITY AND EXPECTED UTILITY WITHOUT ADDITIVITY , 1989 .

[15]  Daniel A. Braun,et al.  Risk-sensitivity and the mean-variance trade-off: decision making in sensorimotor control , 2011, Proceedings of the Royal Society B: Biological Sciences.

[16]  Daniel M. Wolpert,et al.  A modular planar robotic manipulandum with end-point torque control , 2009, Journal of Neuroscience Methods.

[17]  Ken Brodlie,et al.  A Review of Uncertainty in Data Visualization , 2012, Expanding the Frontiers of Visual Analytics and Visualization.

[18]  R. Ivry,et al.  The coordination of movement: optimal feedback control and beyond , 2010, Trends in Cognitive Sciences.

[19]  J. Tallon,et al.  Decision Theory Under Ambiguity , 2012 .

[20]  A. Rustichini,et al.  Ambiguity Aversion, Robustness, and the Variational Representation of Preferences , 2006 .

[21]  Andrew M Colman,et al.  Size doesn't really matter: ambiguity aversion in Ellsberg urns with few balls. , 2008, Experimental psychology.

[22]  Daniel A. Braun,et al.  Learning Optimal Adaptation Strategies in Unpredictable Motor Tasks , 2009, The Journal of Neuroscience.

[23]  A. Tversky,et al.  The framing of decisions and the psychology of choice. , 1981, Science.

[24]  Don A. Moore,et al.  Keeping the illusion of control under control: Ceilings, floors, and imperfect calibration , 2011 .

[25]  Wei Ji Ma,et al.  Bayesian inference with probabilistic population codes , 2006, Nature Neuroscience.

[26]  Stefan Schaal,et al.  Path integral control and bounded rationality , 2011, 2011 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning (ADPRL).

[27]  A. Tversky,et al.  Advances in prospect theory: Cumulative representation of uncertainty , 1992 .

[28]  L. Maloney,et al.  Economic decision-making compared with an equivalent motor task , 2009, Proceedings of the National Academy of Sciences.

[29]  Chris R. Johnson Top Scientific Visualization Research Problems , 2004, IEEE Computer Graphics and Applications.

[30]  Konrad Paul Kording,et al.  Bayesian integration in sensorimotor learning , 2004, Nature.

[31]  Colin Camerer,et al.  Neural Systems Responding to Degrees of Uncertainty in Human Decision-Making , 2005, Science.

[32]  M. Landy,et al.  Decision making, movement planning and statistical decision theory , 2008, Trends in Cognitive Sciences.

[33]  D. Ellsberg Decision, probability, and utility: Risk, ambiguity, and the Savage axioms , 1961 .

[34]  Peter Klibanoff,et al.  Updating Ambiguity Averse Preferences , 2009 .

[35]  Miguel A. Vadillo,et al.  Illusion of Control , 2013, Experimental psychology.

[36]  Alex T. Pang,et al.  Approaches to uncertainty visualization , 1996, The Visual Computer.

[37]  F. Knight The economic nature of the firm: From Risk, Uncertainty, and Profit , 2009 .

[38]  Daniel A. Braun,et al.  The effect of model uncertainty on cooperation in sensorimotor interactions , 2013, Journal of The Royal Society Interface.

[39]  Daniel A. Braun,et al.  Risk-Sensitive Optimal Feedback Control Accounts for Sensorimotor Behavior under Uncertainty , 2010, PLoS Comput. Biol..

[40]  R. J. van Beers,et al.  The role of execution noise in movement variability. , 2004, Journal of neurophysiology.

[41]  Karl J. Friston The free-energy principle: a rough guide to the brain? , 2009, Trends in Cognitive Sciences.

[42]  Taiki Takahashi,et al.  Decision Under Ambiguity: Effects of Sign and Magnitude , 2009, The International journal of neuroscience.

[43]  A. Wald Statistical Decision Functions Which Minimize the Maximum Risk , 1945 .

[44]  Daniel A. Braun,et al.  Information, Utility and Bounded Rationality , 2011, AGI.

[45]  Daniel A. Braun,et al.  Thermodynamics as a theory of decision-making with information-processing costs , 2012, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[46]  Karl J. Friston The free-energy principle: a unified brain theory? , 2010, Nature Reviews Neuroscience.

[47]  M. Landy,et al.  Statistical decision theory and trade-offs in the control of motor response. , 2003, Spatial vision.

[48]  Michael P. Milham,et al.  Distinct neural mechanisms of risk and ambiguity: A meta-analysis of decision-making , 2006, NeuroImage.

[49]  Wei Ji Ma,et al.  Spiking networks for Bayesian inference and choice , 2008, Current Opinion in Neurobiology.

[50]  Konrad Paul Kording,et al.  Decision Theory: What "Should" the Nervous System Do? , 2007, Science.

[51]  Vivien Marx,et al.  Data visualization: ambiguity as a fellow traveler , 2013, Nature Methods.

[52]  Hiroaki Kitano,et al.  Biological robustness , 2008, Nature Reviews Genetics.

[53]  Kip Smith,et al.  Neuronal substrates for choice under ambiguity, risk, gains, and losses , 2001, NeuroImage.

[54]  Massimo Marinacci,et al.  Differentiating ambiguity and ambiguity attitude , 2004, J. Econ. Theory.

[55]  K. Arrow,et al.  Aspects of the theory of risk-bearing , 1966 .

[56]  Daniel A. Braun,et al.  Risk-Sensitivity in Sensorimotor Control , 2011, Front. Hum. Neurosci..