We argue that approaches adhering to normative systems can be as fruitful as those by descriptive systems. In measuring people's perception of randomness, discrepancies between human behavior and normative models could have resulted from unknown properties of the models, and it does not necessarily lead to the conclusion that people are irrational or that the normative system has to be abandoned.

We consider a class of dynamic tournaments in which two contestants are faced with a choice between two courses of action. The first is a riskless option (“hold”) of maintaining the resources the contestant already has accumulated in her turn and ceding the initiative to her rival. The second is the bolder option (“roll”) of taking the initiative of accumulating additional resources, and thereby moving ahead of her rival, while at the same time sustaining a risk of temporary setback. We (...) study this tournament in the context of a jeopardy race game (JRG), extend the JRG to $N > 2$ contestants, and construct its equilibrium solution. Compared to the equilibrium solution, the results of three experiments reveal a dysfunctional bias in favor of the riskless option. This bias is substantially mitigated when the contestants are required to commit in advance how long to pursue the risky course of action. (shrink)

Beliefs like the Gambler's Fallacy and the Hot Hand have interested cognitive scientists, economists, and philosophers for centuries. We propose that these judgment patterns arise from the observer's mental models of the sequence-generating mechanism, moderated by the strength of belief in an a priori base rate. In six behavioral experiments, participants observed one of three mechanisms generating sequences of eight binary events: a random mechanical device, an intentional goal-directed actor, and a financial market. We systematically manipulated participants’ beliefs about the (...) base rate probabilities at which different outcomes were generated by each mechanism. Participants judged 18 sequences of outcomes produced by a mechanism with either an unknown base rate, a specified distribution of three equiprobable base rates, or a precise, fixed base rate. Six target sequences ended in streaks of between two and seven identical outcomes. The most common predictions for subsequent events were best described as pragmatic belief updating, expressed as an increasingly strong expectation that a streak of identical signals would repeat as the length of that streak increased. The exception to this pattern was for sequences generated by a random mechanical device with a fixed base rate of.50. Under this specific condition, participants exhibited a bias toward reversal of streaks, and this bias was larger when participants were asked to make a dichotomous choice versus a numerical probability rating. We review alternate accounts for the anomalous judgments of sequences and conclude with our favored interpretation that is based on Rabin's version of Tversky & Kahneman's Law of Small Numbers. (shrink)

We conduct experiments to analyze investment behavior in decisions under risk. Subjects can bet on the outcomes of a series of coin tosses themselves, rely on randomized ‘experts’, or choose a risk-free alternative. We observe that subjects who rely on the randomized experts pick those who were successful in the past, showing behavior consistent with the hot hand belief. Obviously the term ‘expert’ suffices to attract some subjects. For those who decide on their own, we find behavior consistent with the (...) gambler’s fallacy, as the frequency of betting on heads (tails) decreases after streaks of heads (tails). (shrink)

Normative theories can be useful in developing descriptive theories, as when normative subjective expected utility theory is used to develop descriptive rational choice theory and behavioral game theory. “Ought” questions are also the essence of theories of moral reasoning, a domain of higher mental processing that could not survive without normative considerations.

Erroneous gambling-related beliefs can be defined as beliefs that imply a failure to recognise how commercial gambling activities are designed to generate a guaranteed loss to players. In t...

How to estimate the randomness in random sequence generation tasks? The aim of the paper was to discuss the accuracy of the multiple indexes used for random sequences generation results calculation. In the first part of the paper the models explaining deviations from randomness were presented. The key role of the structural limitations interpretation was suggested. Secondly, the multiple indexes of the deviation from randomness used in random sequence generation task studies were presented. The authors concluded that too many indexes (...) are used in the studies of deviation from randomness. In order to avoid such problems two indexes were proposed: entropy and correlation function. The last part of the paper presents the preliminary version of the mathematical of random sequences generation in which the limited capacity of the short-term memory assumption was introduce. (shrink)

The paper presents a set of games of competition between two or three players in which reward is jointly determined by a stochastic biased mechanism and players’ choices. More specifically, a resource can be found with unequal probabilities in one of two locations. The first agent is rewarded only if it finds the resource and avoids being found by the next agent in line; the latter is rewarded only if it finds the former. Five benchmarks, based on different psychological and (...) game-theoretic assumptions are derived and their predictions compared to actual behavior of 120, 40, and 48 participants playing repeatedly. Of the five benchmarks—the unique (Nash) equilibrium, reinforcement learning, trust-based efficiency, maximum unpredictability, and regret-based (Impulse Balance) equilibrium—regret for missed opportunities best accounts for the qualitative aspect of participants’ behavior and regret attenuated by randomization best accounts for the quantitative aspect of behavior. (shrink)

Although widely investigated and used in psychology, the concept of randomness is beset with philosophical and practical difficulties. In this paper, I propose a resolution to a long-standing problem in psychological research by arguing that the inability to comprehend and produce random behavior is not caused by a defect on the part of the observer but is a consequence of conceptual confusion. Randomness describes a state of high complexity which defies analysis and understanding. The well-known biases in predictive behavior are (...) not caused by the observers’ inability to comprehend randomness but reflect a natural pattern-seeking response to high-complexity situations. Further, I address the circularity at the heart of the randomness debate. Replacing randomness with complexity in psychology and cognitive science would eliminate many of the current problems associated with defining, investigating and using this elusive term. (shrink)

The gambler’s fallacy is the tendency to expect random processes to switch more often than they actually do—for example, to think that after a string of tails, a heads is more likely. It’s often taken to be evidence for irrationality. It isn’t. Rather, it’s to be expected from a group of Bayesians who begin with causal uncertainty, and then observe unbiased data from an (in fact) statistically independent process. Although they converge toward the truth, they do so in an asymmetric (...) way—ruling out “streaky” hypotheses more quickly than “switchy” ones. As a result, the majority (and the average) exhibit the gambler’s fallacy. If they have limited memory, this tendency persists even with arbitrarily-large amounts of data. Indeed, such Bayesians exhibit a variety of the empirical trends found in studies of the gambler’s fallacy: they expect switches after short streaks but continuations after long ones; these nonlinear expectations vary with their familiarity with the causal system; their predictions depend on the sequence they’ve just seen; they produce sequences that are too switchy; and they exhibit greater rates of gambler’s reasoning when forming binary predictions than when forming probability estimates. In short: what’s been thought to be evidence for irrationality may instead be rational responses to limited data and memory. (shrink)