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Rule\u2010based models can exhibit these properties by adhering to 2 principles: that the model gradually learns task\u2010specific rules from instructions and experience, and that bottom\u2010up processing is used whenever possible. In a model of learning perfect time\u2010sharing in dual tasks (Schumacher et al., 2001), speedup learning and bottom\u2010up activation of instructions can explain parallel behavior. In a model of a complex dynamic task (Carnegie Mellon University Aegis Simulation Program [CMU\u2010ASP], Anderson et al., 2004), parallel behavior is explained by the transition from serially organized instructions to rules that are activated by both top\u2010down (goal\u2010driven) and bottom\u2010up (perceptually driven) factors. Parallelism lets the model opportunistically reorder instructions, leading to the gradual emergence of new task strategies.<\/jats:p>","DOI":"10.1207\/s15516709cog0000_23","type":"journal-article","created":{"date-parts":[[2005,6,23]],"date-time":"2005-06-23T14:43:30Z","timestamp":1119537810000},"page":"421-455","update-policy":"http:\/\/dx.doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":38,"title":["Modeling Parallelization and Flexibility Improvements in Skill Acquisition: From Dual Tasks to Complex Dynamic Skills"],"prefix":"10.1111","volume":"29","author":[{"given":"Niels","family":"Taatgen","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2005,5]]},"reference":[{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1037\/0096-3445.117.3.288"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1037\/0033-295X.89.4.369"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1207\/s15516709cog0000_22"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1037\/0033-295X.111.4.1036"},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1037\/0278-7393.23.4.932"},{"key":"e_1_2_1_7_1","unstructured":"Anderson J. 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