A simple artificial life model explains irrational behavior in human decision-making

Exploration and recency as the main proximate causes of probability matching: a reinforcement learning analysis

Research has not yet reached a consensus on why humans match probabilities instead of maximise in a probability learning task. The most influential explanation is that they search for patterns in the random sequence of outcomes. Other explanations, such as expectation matching, are plausible, but do not consider how reinforcement learning shapes people's choices. We aimed to quantify how human performance in a probability learning task is affected by pattern search and reinforcement learning. We collected behavioural data from 84 young adult participants who performed a probability learning task wherein the majority outcome was rewarded with 0.7 probability, and analysed the data using a reinforcement learning model that searches for patterns. Model simulations indicated that pattern search, exploration, recency (discounting early experiences), and forgetting may impair performance. Our analysis estimated that 85% (95% HDI [76, 94]) of participants searched for patterns and believed that each trial outcome depended on one or two previous ones. The estimated impact of pattern search on performance was, however, only 6%, while those of exploration and recency were 19% and 13% respectively. This suggests that probability matching is caused by uncertainty about how outcomes are generated, which leads to pattern search, exploration, and recency.

Group-wise herding behavior in financial markets: an agent-based modeling approach

In this paper, we shed light on the dynamic characteristics of rational group behaviors and the relationship between monetary policy and economic units in the financial market by using an agent-based model (ABM), the Hurst exponent, and the Shannon entropy. First, an agent-based model is used to analyze the characteristics of the group behaviors at different levels of irrationality. Second, the Hurst exponent is applied to analyze the characteristics of the trend-following irrationality group. Third, the Shannon entropy is used to analyze the randomness and unpredictability of group behavior. We show that in a system that focuses on macro-monetary policy, steep fluctuations occur, meaning that the medium-level irrationality group has the highest Hurst exponent and Shannon entropy among all of the groups. However, in a system that focuses on micro-monetary policy, all group behaviors follow a stable trend, and the medium irrationality group thus remains stable, too. Likewise, in a system that focuses on both micro- and macro-monetary policies, all groups tend to be stable. Consequently, we find that group behavior varies across economic units at each irrationality level for micro- and macro-monetary policy in the financial market. Together, these findings offer key insights into monetary policy.

Decision-making theories: linking the disparate research areas of individual and collective cognition

In order to maximize their fitness, animals have to deal with different environmental and social factors that affect their everyday life. Although the way an animal behaves might enhance its fitness or survival in regard to one factor, it could compromise them regarding another. In the domain of decision sciences, research concerning decision making focuses on performances at the individual level but also at the collective one. However, between individual and collective decision making, different terms are used resulting in little or no connection between both research areas. In this paper, we reviewed how different branches of decision sciences study the same concept, mainly called speed-accuracy trade-off, and how the different results are on the same track in terms of showing the optimality of decisions. Whatever the level, individual or collective, each decision might be defined with three parameters: time or delay to decide, risk and accuracy. We strongly believe that more progress would be possible in this domain of research if these different branches were better linked, with an exchange of their results and theories. A growing amount of literature describes economics in humans and eco-ethology in birds making compromises between starvation, predation and reproduction. Numerous studies have been carried out on social cognition in primates but also birds and carnivores, and other publications describe market or reciprocal exchanges of commodities. We therefore hope that this paper will lead these different areas to a common decision science.