This thesis is an investigation of how subjects behave in an individual binary choice decision task with the option to purchase or observe for free additional information before reaching a decision. In part 1 of this thesis, an investigative study is conducted with the intent to sharpen the view to literature concerning corresponding psychology and economics experiments designed to test decision tasks that involve purchasing and observing information from an imperfect message prior to taking a terminal action choice. This investigative study identifies areas of research that warrant further investigation as well as provides enhancements for execution in the subsequent experiment conducted in Part 2 & 3 of this thesis. In Part 2 & 3, I conduct an experiment to test how subjects behave in an individual binary choice decision task with the option to purchase or observe for free additional information before reaching a final decision. I find that subjects’ behaviour over time converges toward optimal decisions prior to observing an imperfect information signal. However, when subjects observe an imperfect information signal prior to their terminal choice there is greater deviation from optimal behaviour. I find in addition to behaviour that is reflective of a risk-neutral BEU maximizer, status quo bias, over-weighing the informational value of the message received and past statistically independent outcomes influencing future choices. The subjects’ willingness to pay (WTP) to use the additional information gathered from an imperfect message service when making a final decision was on average less than the risk neutral BEU willingness to pay benchmark. Moreover, as the informative value of the message increased, causing the BEU valuation to increase, subjects under-estimated the value of the message signal to a greater degree. Although risk attitudes may have influenced the subjects’ WTP decisions, it does not account for the increased conservative WTP behaviour when information became more valuable. Additionally, the findings from this study suggest that individuals adopt different decision rules depending on both personal attributes (i.e. skillset, gender, experience) and on the context and environment in which the decision task is conducted. / SSHRC grant: Social Sciences and Humanities Research Council via Dr. Bram Cadsby Professor Department of Economics, University of Guelph

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Le sentiment d’agentivité est défini comme le sentiment de contrôler nos actions, et à travers elles, les évènements du monde extérieur. Cet ensemble phénoménologique dépend de notre capacité d’apprendre les contingences entre nos actions et leurs résultats, et un algorithme classique pour modéliser cela vient du domaine de l’apprentissage par renforcement. Dans cette thèse, nous avons utilisé l’approche de modélisation cognitive pour étudier l’interaction entre agentivité et apprentissage par renforcement. Tout d’abord, les participants réalisant une tâche d’apprentissage par renforcement tendent à avoir plus d’agentivité. Cet effet est logique, étant donné que l’apprentissage par renforcement consiste à associer une action volontaire et sa conséquence. Mais nous avons aussi découvert que l’agentivité influence l’apprentissage de deux manières. Le mode par défaut pour apprendre des contingences action-conséquence est que nos actions ont toujours un pouvoir causal. De plus, simplement choisir une action change l’apprentissage de sa conséquence. En conclusion, l’agentivité et l’apprentissage par renforcement, deux piliers de la psychologie humaine, sont fortement liés. Contrairement à des ordinateurs, les humains veulent être en contrôle, et faire les bons choix, ce qui biaise notre aquisition d’information. / Sense of agency or subjective control can be defined by the feeling that we control our actions, and through them effects in the outside world. This cluster of experiences depend on the ability to learn action-outcome contingencies and a more classical algorithm to model this originates in the field of human reinforcementlearning. In this PhD thesis, we used the cognitive modeling approach to investigate further the interaction between perceived control and reinforcement learning. First, we saw that participants undergoing a reinforcement-learning task experienced higher agency; this influence of reinforcement learning on agency comes as no surprise, because reinforcement learning relies on linking a voluntary action and its outcome. But our results also suggest that agency influences reinforcement learning in two ways. We found that people learn actionoutcome contingencies based on a default assumption: their actions make a difference to the world. Finally, we also found that the mere fact of choosing freely shapes the learning processes following that decision. Our general conclusion is that agency and reinforcement learning, two fundamental fields of human psychology, are deeply intertwined. Contrary to machines, humans do care about being in control, or about making the right choice, and this results in integrating information in a one-sided way.