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

The LHCb upgrade I

The LHCb upgrade represents a major change of the experiment. The detectors have been almost completely renewed to allow running at an instantaneous luminosity five times larger than that of the previous running periods. Readout of all detectors into an all-software trigger is central to the new design, facilitating the reconstruction of events at the maximum LHC interaction rate, and their selection in real time. The experiment's tracking system has been completely upgraded with a new pixel vertex detector, a silicon tracker upstream of the dipole magnet and three scintillating fibre tracking stations downstream of the magnet. The whole photon detection system of the RICH detectors has been renewed and the readout electronics of the calorimeter and muon systems have been fully overhauled. The first stage of the all-software trigger is implemented on a GPU farm. The output of the trigger provides a combination of totally reconstructed physics objects, such as tracks and vertices, ready for final analysis, and of entire events which need further offline reprocessing. This scheme required a complete revision of the computing model and rewriting of the experiment's software

Exploring land use trends in Europe: a comparison of forecasting approaches and results.

Over the past years several studies have explored future land use trends for Europe. This paper presents a comparison of six land use studies for Europe that explore land use changes until 2020/2030. We compared these studies with respect to qualitative as well as quantitative aspects. The qualitative analysis shows that many studies focus on agricultural land uses and therefore draw on detailed agricultural models, while only few include urban developments. The purpose of about half of the studies is to provide land use outlooks, while the other half used scenarios to test the behaviour of scientific models or show their potential applicability. For the quantitative comparison we considered the results of their reference and alternative scenarios. This comparison shows that there is a large difference between the projected results provided by the different outlooks. We even found that alternative scenario outcomes within a single outlook study are more similar than the results of reference scenarios between outlook studies. To a large extent this can be traced back to the differences in initial data sources, data pre-processing and model assumptions. To exclude the impact of differences in initial data, also relative changes were computed. Results from this analysis show a large range of values, which indicates a large uncertainty in the results of land use outlooks. We suggest using all results as the plausibility space for future land use changes. Many studies have kept the values of drivers within a rather limited range, while in reality larger shocks may well be possible