<?xml version="1.0" encoding="UTF-8" ?><xml><records><record><database name="!wdg&apos;s ref list_v8.enl" path="/Users/gray/Documents/!wdg&apos;s ref list_v8.enl">!wdg&apos;s ref list_v8.enl</database><source-app name="EndNote" version="10.0">EndNote</source-app><rec-number>1935</rec-number><ref-type name="Journal Article">17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Fu, Wai-Tat</style></author><author><style face="normal" font="default" size="100%">Gray, Wayne D.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Suboptimal tradeoffs in information seeking</style></title><secondary-title><style face="normal" font="default" size="100%">Cognitive Psychology</style></secondary-title></titles><periodical><full-title><style face="normal" font="default" size="100%">Cognitive Psychology</style></full-title></periodical><pages><style face="normal" font="default" size="100%">195-242</style></pages><volume><style face="normal" font="default" size="100%">52</style></volume><number><style face="normal" font="default" size="100%">3</style></number><reprint-edition><style face="normal" font="default" size="100%">FG_SOTIS-R1.doc</style></reprint-edition><keywords><keyword><style face="normal" font="default" size="100%">Problem solving</style></keyword><keyword><style face="normal" font="default" size="100%">Adaptive search</style></keyword><keyword><style face="normal" font="default" size="100%">Information seeking</style></keyword><keyword><style face="normal" font="default" size="100%">Suboptimal tradeoffs</style></keyword><keyword><style face="normal" font="default" size="100%">Satisficing, Bayesian learning</style></keyword><keyword><style face="normal" font="default" size="100%">ACT-R</style></keyword><keyword><style face="normal" font="default" size="100%">Cognitive modeling</style></keyword><keyword><style face="normal" font="default" size="100%">Sequential decision making</style></keyword></keywords><dates><year><style face="normal" font="default" size="100%">2006</style></year></dates><abstract><style face="normal" font="default" size="100%">Explicit information-seeking actions are needed to evaluate alternative actions in problem-solving tasks. Information-seeking costs are often traded off against the utility of information. We present three experiments that show how subjects adapt to the cost and information structures of environments in a map-navigation task. We found that subjects often stabilize at suboptimal levels of performance. A Bayesian satisficing model (BSM) is proposed and implemented in the ACT-R architecture to predict information-seeking behavior. The BSM uses a local decision rule and a global Bayesian learning mechanism to decide when to stop seeking information. The model matched the human data well, suggesting that adaptation to cost and information structures can be achieved by a simple local decision rule. The local decision rule, however, often limits exploration of the environment and leads to suboptimal performance. We propose that suboptimal performance is an emergent property of the dynamic interactions between cognition and the environment.</style></abstract><notes><style face="normal" font="default" size="100%">Funded by:&#xD;AFOSR&#xD;</style></notes><urls><pdf-urls><url><style face="normal" font="default" size="100%">internal-pdf://Fu&amp;Gray06_CP-1845985024/Fu&amp;Gray06_CP.pdf</style></url></pdf-urls></urls><electronic-resource-num><style face="normal" font="default" size="100%">DOI information: 10.1016/j.cogpsych.2005.08.002</style></electronic-resource-num><research-notes><style face="normal" font="default" size="100%">AFOSR</style></research-notes></record></records></xml>