PLANNING ROUTES ACROSS ECONOMIC TERRAINS: MAXIMIZING UTILITY, FOLLOWING HEURISTICS
We designed an economic task to investigate human planning of routes in landscapes where travel in different kinds of terrain incurs different costs. Participants moved their finger across a touch screen from a starting point to a destination. The screen was divided into distinct kinds of terrain an...
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doaj-f84525b2f4de4ddd9248316397072b6d2020-11-24T22:12:59ZengFrontiers Media S.A.Frontiers in Psychology1664-10782010-12-01110.3389/fpsyg.2010.002147155PLANNING ROUTES ACROSS ECONOMIC TERRAINS: MAXIMIZING UTILITY, FOLLOWING HEURISTICSHang eZhang0Hang eZhang1Soumya V Maddula2Laurence T Maloney3Laurence T Maloney4New York UniversityNew York UniversityNew York UniversityNew York UniversityNew York UniversityWe designed an economic task to investigate human planning of routes in landscapes where travel in different kinds of terrain incurs different costs. Participants moved their finger across a touch screen from a starting point to a destination. The screen was divided into distinct kinds of terrain and travel within each kind of terrain imposed a cost proportional to distance traveled. We varied costs and spatial configurations of terrains and participants received fixed bonuses minus the total cost of the routes they chose. We first compared performance to a model maximizing gain. All but one of 12 participants failed to adopt least-cost routes and their failure to do so reduced their winnings by about 30% (median value). We tested in detail whether participants’ choices of routes satisfied three necessary conditions (heuristics) for a route to maximize gain. We report failures of one heuristic for 7 out of 12 participants. Last of all, we modeled human performance with the assumption that participants assign subjective utilities to costs and maximize utility. For 7 out 12 participants, the fitted utility function was an accelerating power function of actual cost and for the remaining 5, a decelerating power function. We discuss connections between utility aggregation in route planning and decision under risk. Our task could be adapted to investigate human strategy and optimality of route planning in full-scale landscapes.http://journal.frontiersin.org/Journal/10.3389/fpsyg.2010.00214/fullDecision MakingnavigationBayesian decision theoryHeuristicsoptimalityroute selection |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Hang eZhang Hang eZhang Soumya V Maddula Laurence T Maloney Laurence T Maloney |
spellingShingle |
Hang eZhang Hang eZhang Soumya V Maddula Laurence T Maloney Laurence T Maloney PLANNING ROUTES ACROSS ECONOMIC TERRAINS: MAXIMIZING UTILITY, FOLLOWING HEURISTICS Frontiers in Psychology Decision Making navigation Bayesian decision theory Heuristics optimality route selection |
author_facet |
Hang eZhang Hang eZhang Soumya V Maddula Laurence T Maloney Laurence T Maloney |
author_sort |
Hang eZhang |
title |
PLANNING ROUTES ACROSS ECONOMIC TERRAINS: MAXIMIZING UTILITY, FOLLOWING HEURISTICS |
title_short |
PLANNING ROUTES ACROSS ECONOMIC TERRAINS: MAXIMIZING UTILITY, FOLLOWING HEURISTICS |
title_full |
PLANNING ROUTES ACROSS ECONOMIC TERRAINS: MAXIMIZING UTILITY, FOLLOWING HEURISTICS |
title_fullStr |
PLANNING ROUTES ACROSS ECONOMIC TERRAINS: MAXIMIZING UTILITY, FOLLOWING HEURISTICS |
title_full_unstemmed |
PLANNING ROUTES ACROSS ECONOMIC TERRAINS: MAXIMIZING UTILITY, FOLLOWING HEURISTICS |
title_sort |
planning routes across economic terrains: maximizing utility, following heuristics |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Psychology |
issn |
1664-1078 |
publishDate |
2010-12-01 |
description |
We designed an economic task to investigate human planning of routes in landscapes where travel in different kinds of terrain incurs different costs. Participants moved their finger across a touch screen from a starting point to a destination. The screen was divided into distinct kinds of terrain and travel within each kind of terrain imposed a cost proportional to distance traveled. We varied costs and spatial configurations of terrains and participants received fixed bonuses minus the total cost of the routes they chose. We first compared performance to a model maximizing gain. All but one of 12 participants failed to adopt least-cost routes and their failure to do so reduced their winnings by about 30% (median value). We tested in detail whether participants’ choices of routes satisfied three necessary conditions (heuristics) for a route to maximize gain. We report failures of one heuristic for 7 out of 12 participants. Last of all, we modeled human performance with the assumption that participants assign subjective utilities to costs and maximize utility. For 7 out 12 participants, the fitted utility function was an accelerating power function of actual cost and for the remaining 5, a decelerating power function. We discuss connections between utility aggregation in route planning and decision under risk. Our task could be adapted to investigate human strategy and optimality of route planning in full-scale landscapes. |
topic |
Decision Making navigation Bayesian decision theory Heuristics optimality route selection |
url |
http://journal.frontiersin.org/Journal/10.3389/fpsyg.2010.00214/full |
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