Summary of simulations and results.

<p>Each line represents a different model composed of a pair of Reinforcement Learning systems. Each column represents a simulated experiment. Experiments are grouped by the kind of data accounted for: behavioural (autoshaping <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003466#pcbi.1003466-Flagel1" target="_blank">[14]</a>, <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003466#pcbi.1003466-Flagel3" target="_blank">[21]</a>, CRE <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003466#pcbi.1003466-Robinson1" target="_blank">[22]</a>, Incentive salience <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003466#pcbi.1003466-Mahler1" target="_blank">[23]</a>, <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003466#pcbi.1003466-DiFeliceantonio1" target="_blank">[24]</a>), physiological <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003466#pcbi.1003466-Flagel3" target="_blank">[21]</a> and pharmacological (Flu post-NAcC <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003466#pcbi.1003466-Saunders1" target="_blank">[25]</a>, Flu pre-systemic <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003466#pcbi.1003466-Flagel3" target="_blank">[21]</a>). Variant 4 (i.e. Model-based/Model-Free without features) is not included as it failed to even reproduce the autoshaping behavioural results and was not investigated further.