3,231 research outputs found
The Mythology of Game Theory
Non-cooperative game theory is at its heart a theory of cognition, specifically a theory of how decisions are made. Game theory\u27s leverage is that we can design different payoffs, settings, player arrays, action possibilities, and information structures, and that these differences lead to different strategies, outcomes, and equilibria. It is well-known that, in experimental settings, people do not adopt the predicted strategies, outcomes, and equilibria. The standard response to this mismatch of prediction and observation is to add various psychological axioms to the game-theoretic framework. Regardless of the differing specific proposals and results, game theory uniformly makes certain cognitive assumptions that seem rarely to be acknowledged, much less interrogated. Indeed, it is not widely understood that game theory is essentially a cognitive theory. Here, we interrogate those cognitive assumptions. We do more than reject specific predictions from specific games. More broadly, we reject the underlying cognitive model implicitly assumed by game theory
How simple rules determine pedestrian behavior and crowd disasters
With the increasing size and frequency of mass events, the study of crowd
disasters and the simulation of pedestrian flows have become important research
areas. Yet, even successful modeling approaches such as those inspired by
Newtonian force models are still not fully consistent with empirical
observations and are sometimes hard to calibrate. Here, a novel cognitive
science approach is proposed, which is based on behavioral heuristics. We
suggest that, guided by visual information, namely the distance of obstructions
in candidate lines of sight, pedestrians apply two simple cognitive procedures
to adapt their walking speeds and directions. While simpler than previous
approaches, this model predicts individual trajectories and collective patterns
of motion in good quantitative agreement with a large variety of empirical and
experimental data. This includes the emergence of self-organization phenomena,
such as the spontaneous formation of unidirectional lanes or stop-and-go waves.
Moreover, the combination of pedestrian heuristics with body collisions
generates crowd turbulence at extreme densities-a phenomenon that has been
observed during recent crowd disasters. By proposing an integrated treatment of
simultaneous interactions between multiple individuals, our approach overcomes
limitations of current physics-inspired pair interaction models. Understanding
crowd dynamics through cognitive heuristics is therefore not only crucial for a
better preparation of safe mass events. It also clears the way for a more
realistic modeling of collective social behaviors, in particular of human
crowds and biological swarms. Furthermore, our behavioral heuristics may serve
to improve the navigation of autonomous robots.Comment: Article accepted for publication in PNA
The value-added of primary schools: what is it really measuring?
This paper compares the official value-added scores in 2005 for all primary schools in three adjacent LEAs in England with the raw-score Key Stage 2 results for the same schools. The correlation coefficient for the raw- and value-added scores of these 457 schools is around +0.75. Scatterplots show that there are no low attaining schools with average or higher value-added, and no high attaining schools with below average value-added. At least some of the remaining scatter is explained by the small size of some schools. Although some relationship between these measures is to be expected – so that schools adding considerable value would tend to have high examination outcome scores – the relationship shown is too strong for this explanation to be considered sufficient. Value-added analysis is intended to remove the link between a schools’ intake scores and their raw-score outcomes at KS2. It should lead to an estimate of the differential progress made by pupils, assessed between schools. In fact, however, the relationship between value-added and raw scores is of the same size as the original relationship between intake scores and raw-scores that the value-added is intended to overcome. Therefore, however appealing the calculation of value-added figures is, their development is still at the stage where they are not ready to move from being a research tool to an instrument of judgement on schools. Such figures may mislead parents, governors and teachers and, even more importantly, they are being used in England by OFSTED to pre-determine the results of school inspections
Pareto Optimal Matchings in Many-to-Many Markets with Ties
We consider Pareto-optimal matchings (POMs) in a many-to-many market of
applicants and courses where applicants have preferences, which may include
ties, over individual courses and lexicographic preferences over sets of
courses. Since this is the most general setting examined so far in the
literature, our work unifies and generalizes several known results.
Specifically, we characterize POMs and introduce the \emph{Generalized Serial
Dictatorship Mechanism with Ties (GSDT)} that effectively handles ties via
properties of network flows. We show that GSDT can generate all POMs using
different priority orderings over the applicants, but it satisfies truthfulness
only for certain such orderings. This shortcoming is not specific to our
mechanism; we show that any mechanism generating all POMs in our setting is
prone to strategic manipulation. This is in contrast to the one-to-one case
(with or without ties), for which truthful mechanisms generating all POMs do
exist
Plasticity facilitates sustainable growth in the commons
In the commons, communities whose growth depends on public goods, individuals
often rely on surprisingly simple strategies, or heuristics, to decide whether
to contribute to the common good (at risk of exploitation by free-riders).
Although this appears a limitation, here we show how four heuristics lead to
sustainable growth by exploiting specific environmental constraints. The two
simplest ones --contribute permanently or switch stochastically between
contributing or not-- are first shown to bring sustainability when the public
good efficiently promotes growth. If efficiency declines and the commons is
structured in small groups, the most effective strategy resides in contributing
only when a majority of individuals are also contributors. In contrast, when
group size becomes large, the most effective behavior follows a minimal-effort
rule: contribute only when it is strictly necessary. Both plastic strategies
are observed in natural systems what presents them as fundamental social motifs
to successfully manage sustainability
The role of data visualization in Railway Big Data Risk Analysis
Big Data Risk Analysis (BDRA) is one of the possible alleys for the further development of risk models in the railway transport. Big Data techniques allow a great quantity of information to be handled from different types of sources (e.g. unstructured text, signaling and train data). The benefits of this approach may lie in improving the understanding of the risk factors involved in railways, detecting possible new threats or assessing the risk levels for rolling stock, rail infrastructure or railway operations. For the efficient use of BDRA, the conversion of huge amounts of data into a simple and effective display is particularly challenging. Especially because it is presented to various specific target audiences. This work reports a literature review of risk communication and visualization in order to find out its applicability to BDRA, and beyond the visual techniques, what human factors have to be considered in the understanding and risk perception of the infor-mation when safety analysts and decision-makers start basing their decisions on BDRA analyses. It was found that BDRA requires different visualization strategies than those that have normally been carried out in risk analysis up to now
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