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Most decision-making studies will focus on the value and uncertainty of each choice option but do not focus on the importance of the representation of the choice option itself. This thesis presents the effects that task goals have on creating the appropriate cognitive representation to achieve those goals and how these representations are dependent on the informational input within a given task. The overall hypothesis for this work is that cognitive representations reveal a trade-off between accommodating task goals and the format of the information sampled from the environment of the task. For example, ordering books in a stand in alphabetical order, to facilitate the task of retrieving a relevant one when necessary, reveals a material implication of such cognitive representations. As in many situations, the internal representations constructed by the agent embody the remaining degrees of freedom that map the input to successful task completion. The first two chapters in this work present how uncertain beliefs about ourselves and our preferences are either integrated or compared to fixed information about other agent’s beliefs. The third chapter presents the direct manipulation of representations of choice options by changing both the stimuli and controlling for the decision strategy used by the decision-makers. The fourth chapter presents how choice options themselves are represented in the human brain. The findings related to 1) the adaptation of personal preferences and beliefs to the (fixed) preferences and beliefs of other agents, 2) observed reduction in decision strategy compliance contingent on stimulus format, and 3) the task-contingent results for similarities between brain states of choice options, support the general trade-off hypothesis. The conclusion that can be drawn is that the study of choice option representations is underdetermined unless both informational input and task goals are accounted for.

This thesis investigates human probabilistic judgment in complex real-world settings to identify processes underpinning biases across groups which relate to numerical frames and formats. Experiments are conducted replicating real-world environments and data to test judgment performance based on framing and format. Regardless of background skills and experience, people in professional and consumer contexts show a strong tendency to perceive the world from a linear perspective, interpreting information in concrete, absolute terms and making judgments based on seeking and applying linear functions. Whether predicting sales, selecting between financial products, or forecasting refugee camp data, people use minimal cues and systematically apply additive methods amidst non-linear trends and percentage points to yield linear estimates in both rich and sparse informational contexts. Depending on data variability and temporality, human rationality and choice may be significantly helped or hindered by informational framing and format. The findings deliver both theoretical and practical contributions. Across groups and individual differences, the effects of informational format and the tendency to linearly extrapolate are connected by the bias to perceive values in concrete terms and make sense of data by seeking simple referent points. People compare and combine referents using additive methods when inappropriate and adhere strongly to defaults when applied in complex numeric environments. The practical contribution involves a framing manipulation which shows that format biases (i.e., additive processing) and optimism (i.e., associated with intertemporal effects) can be counteracted in judgments involving percentages and exponential growth rates by using absolute formats and positioning defaults in future event context information. This framing manipulation was highly effective in improving loan choice and repayment judgments compared to information in standard finance industry formats. There is a strong potential to increase rationality using this data format manipulation in other financial settings and domains such as health behaviour change in which peoples’ erroneous interpretation of percentages and non-linear relations negatively impact choice and behaviours in both the short and long-term.

When making decisions under uncertainty, one common view is that people rely on simple heuristics that deliberately ignore information. One of the greatest puzzles in cognitive science concerns why heuristics can sometimes outperform full-information models, such as linear regression, which make full use of the available information. In this thesis, I will contribute the novel idea that heuristics can be thought of as embodying extreme Bayesian priors. Thereby, an explanation for less-is-more is that the heuristics’ relative simplicity and inflexibility amounts to a strong inductive bias, that is suitable for some learning and decision problems. I will formalize this idea by introducing Bayesian models within which heuristics are an extreme case along a continuum of model flexibility defined by the strength and nature of the prior. Crucially, the Bayesian models include heuristics at one of the Bayesian prior strength and classic full-information models at the other end of the Bayesian prior. This allows for a comparative test between the intermediate models along the continuum and the extremes of heuristics and full regression model. Indeed, I will show that intermediate models perform best across simulations, suggesting that down-weighting information is preferable to entirely ignoring it. These results refute an absolute version of less-is-more, demonstrating that heuristics will usually be outperformed by a model that takes into account the full information but weighs it appropriately. Thereby, the thesis provides a novel explanation for less-is-more: Heuristics work well because they embody a Bayesian prior that approximates the optimal prior. While the main contribution is formal, the final Chapter will explore whether less is more at the psychological level, and finds that people do not use heuristics, but rely on the full information instead. A consistent perspective will emerge throughout the whole thesis, which is that less is not more.

Should I get chocolate ice cream as usual or try the lemon-chocolate mix from the weekly special? Everybody frequently faces the choice between well-known options (i.e. exploiting) and alternatives that potentially best current favourites (i.e. exploring). Previous research showed that, even in changing environments, people are able to effectively balance exploration and exploitation. However, some presumably influential factors for human exploratory behaviour in complex, real world environments have not gained enough attention in the literature. In the present work, we will discuss the potential impact of three such factors on people's exploratory decision-making. First, we focus on noisy information and the fact that humans often obtain both, relevant and irrelevant information to make exploratory decisions. We present experimental evidence supporting the idea that people are able to ignore misleading information that is irrelevant for effective exploratory decision- making. Aside from noisy information about choice outcomes, people are often able to observe their peers making similar decisions or even face decisions as a group. A further study therefore examines how people use information about others' decisions to make their own exploratory choices. Though mostly advantageous, social information can also lead to bad decisions in some cases. Lastly, while most lab studies involve decisions with objective outcomes (e.g. money), many real world decisions require people to interpret outcomes subjectively (e.g. the taste of food). Two lab experiments, together with field data involving choices of more than 380,000 supermarket customers over 250 weeks suggest that people explore choices with subjective outcomes in a manner counter to the normative predictions for objective outcomes. The findings support the idea that people's choices change their preferences, inducing coherency-maximizing behaviour where exploration becomes less likely the longer individuals have been exploiting recently.