Advanced machine learning has achieved extraordinary success in recent years. “Active” operational risk beyond ex post analysis of measured-data machine learning could provide help beyond the regime of traditional statistical analysis when it comes to the “known unknown” or even the...

We examine the various senses in which economist use the term "rationality" and then outline some of the commonly drawn implications and auxiliary assumptions. Finally, we confront the implications with the empirical evidence, drawing on the insights from the exciting new field of behavioral...

This work challenges the very notion of bounded rationality as dangerously too near to some "unbounded rationality" used as a benchmark. Should we assume that there is an "unbounded" rationality as a benchmark? Should one start, in order to describe and interpret human behaviour, from a model...

We consider a novel generalization of the resource-constrained project scheduling problem (RCPSP). Unlike many established approaches for the RCPSP that aim to minimize the makespan of the project for given static capacity constraints, we consider the important real-life aspect that capacity...

We analyze the individual and macroeconomic impacts of heterogeneous expectations and action rules within an agent-based model populated by heterogeneous, interacting firms. Agents have to cope with a complex evolving economy characterized by deep uncertainty resulting from technical change,...

Heuristics based on dispatching rules are still widely used in practice as methods for effective scheduling systems. Despite the successful development of various novel dispatching rules for traditional job shop scheduling environments, nearly none of these has been applied to cellular...

This paper tests an intervention aimed at facilitating (cognitively) the adoption of healthy dietary habits. We provide easy-to-understand information about the risks of developing diabetes or heart diseases and give easy-to-follow dietary recommendations to minimize these risks. We implement...

Geothermal plants have been increasingly constructed in recent years to exploit the high geothermal energy potential in Germany in district heating networks at the municipal level. In order to use this potential economically, municipal planners need instruments for designing the district heating...

We investigate a recently introduced extension of the multi-period facility location problem that considers service-differentiated customer segments. Accordingly, some customers require their demands to be met on time, whereas the remaining customers accept delayed deliveries as long as lateness...

In this paper, we take a comprehensive and multidisciplinary look at terrorism sentencing decisions over a 17-year period, between September 2001 when the ATA was first conceived of and September 2018. In so doing, we first offer an empirical analysis of the sentences for all terrorism offenses...

I study the path properties of adaptive heuristics that mimic the natural dynamics of play in a game and converge to the set of correlated equilibria. Despite their apparent differences, I show that these heuristics have an abstract representation as a sequence of probability distributions that...

We investigate whether short-term everyday stressors leads to unhealthier dietary choices among low socioeconomic status mothers. We propose a novel stress protocol that aims to mimic everyday stressors experienced by this population, involving time and financial pressure. We evaluate the impact...

Behavioral and experimental literature on financial instability focuses on either subjective price expectations (Learning-to-Forecast experiments) or individual trading (Learning-to-Optimize experiments). Bao et al. (2017) have shown that subjects have problems with both tasks. In this paper, I...

For most computationally intractable problems there exists no heuristic which performs best on all instances. Usually, a heuristic characterized as best will perform good on the majority of instances but leave a minority on which other heuristics do better. In priority rule-based scheduling,...

This paper analyzes 12,596 wagering decisions of 6,064 contestants in the US game show Jeopardy!, focusing on the anchoring phenomenon in financial decision-making. We find that contestants anchor heavily on the initial dollar value of a clue in their wagering decision, even though there exists...

We study the role of heuristic versus deliberative processing in intertemporal choice. Using studies in the Democratic Republic of Congo and an online labor market, we show that waiting periods - designed to prompt deliberation by temporally separating news about choice sets from choices...

In strategic situations, humans infer the state of mind of others, e.g., emotions or intentions, adapting their behavior appropriately. Nonetheless, evolutionary studies of cooperation typically focus only on reaction norms, e.g., tit for tat, whereby individuals make their next decisions by...

In this paper I study the relationship between rationality and asset prices when agents have heterogeneous and incorrect beliefs about future events. Using the fully rational pricing as a benchmark, I show that when agents behave according to the Subjective Generalized Kelly rule (Bottazzi et...

This work challenges the very notion of bounded rationality as dangerously too near to some "unbounded rationality" used as a benchmark. Should we assume that there is an "unbounded" rationality as a benchmark? Should one start, in order to describe and interpret human behaviour, from a model...

This study considers instant decision-making needs of the automobile manufactures for resequencing vehicles before final assembly (FA). We propose a rule-based two-stage stochastic model to determine the number of spare vehicles that should be kept in the pre-assembly buffer to restore the...

Advanced machine learning has achieved extraordinary success in recent years. 'Active' operational risk beyond ex post analysis of measured-data machine learning could provide help beyond the regime of traditional statistical analysis when it comes to the 'known unknown' or even the 'unknown...

We examine the various senses in which economist use the term “rationality” and then outline some of the commonly drawn implications and auxiliary assumptions. Finally, we confront the implications with the empirical evidence, drawing on the insights from the exciting new field of behavioral...

Modeling the interactions between a reinsurer and several insurers, or between a central management branch (CB) and several subsidiary business branches, or between a coalition and its members, are fascinating problems, which suggest many interesting questions. Beyond two dimensions, one cannot...

In this paper I study the relationship between rationality and asset prices when agents have heterogeneous and incorrect beliefs about future events. Using the fully rational pricing as a benchmark, I show that when agents behave according to the Subjective Generalized Kelly rule (Bottazzi et...

This survey discusses behavioral and experimental macroeconomics emphasizing a complex systems perspective. The economy consists of boundedly rational heterogeneous agents who do not fully understand their complex environment and use simple decision heuristics. Central to our survey is the...

This study extends the hybrid version of the baseline New-Keynesian model with heterogeneous agents who may adopt various forecast heuristics. With a focus on consumer expectations, we identify the most appropriate pairs of forecast heuristics that can lead to an equivalent fit to the data...

In this study, we analyze the macroeconomic dynamics under various shocks in two competing frameworks. Given the baseline New-Keynesian model, we compare the impulse response functions that stem from the hybrid version under rational expectations with the ones obtained in the forward-looking...

In this paper, we introduce the simulated maximum likelihood method for identifying behavioral heuristics of heterogeneous agents in the baseline three-equation New Keynesian model. The method is extended to multivariate macroeconomic optimization problems, and the estimation pro-cedure is...

We consider a novel generalization of the resource-constrained project scheduling problem (RCPSP). Unlike many established approaches for the RCPSP that aim to minimize the makespan of the project for given static capacity constraints, we consider the important real-life aspect that capacity...

This study considers instant decision-making needs of the automobile manufactures for resequencing vehicles before final assembly (FA). We propose a rule-based two-stage stochastic model to determine the number of spare vehicles that should be kept in the pre-assembly buffer to restore the...