Understanding responses to environments for the Prisoner's Dilemma: A meta analysis, multidimensional optimisation and machine learning approach

This thesis investigates the behaviour that Iterated Prisoner’s Dilemma strategies should adopt as a response to different environments. The Iterated Prisoner’s Dilemma (IPD) is a particular topic of game theory that has attracted academic attention due to its applications in the understanding of the balance between cooperation and com petition in social and biological settings. This thesis uses a variety of mathematical and computational fields such as linear al gebra, research software engineering, data mining, network theory, natural language processing, data analysis, mathematical optimisation, resultant theory, markov mod elling, agent based simulation, heuristics and machine learning. The literature around the IPD has been exploring the performance of strategies in the game for years. The results of this thesis contribute to the discussion of successful performances using various novel approaches. Initially, this thesis evaluates the performance of 195 strategies in 45,600 computer tournaments. A large portion of the 195 strategies are drawn from the known and named strategies in the IPD literature, including many previous tournament winners. The 45,600 computer tournaments include tournament variations such as tournaments with noise, probabilistic match length, and both noise and probabilistic match length. This diversity of strategies and tournament types has resulted in the largest and most diverse collection of computer tournaments in the field. The impact of features on the performance of the 195 strategies is evaluated using modern machine learning and statistical techniques. The results reinforce the idea that there are properties associated with success, these are: be nice, be provocable and generous, be a little envious, be clever, and adapt to the environment. Secondly, this thesis explores well performed behaviour focused on a specific set of IPD strategies called memory-one, and specifically a subset of them that are considered extortionate. These strategies have gained much attention in the research field and have been acclaimed for their performance against single opponents. This thesis uses mathematical modelling to explore the best responses to a collection of memory-one strategies as a multidimensional non-linear optimisation problem, and the benefits of extortionate/manipulative behaviour. The results contribute to the discussion that behaving in an extortionate way is not the optimal play in the IPD, and provide evidence that memory-one strategies suffer from their limited memory in multi agent interactions and can be out performed by longer memory strategies. Following this, the thesis investigates best response strategies in the form of static sequences of moves. It introduces an evolutionary algorithm which can successfully identify best response sequences, and uses a list of 192 opponents to generate a large data set of best response sequences. This data set is then used to train a type of recurrent neural network called the long short-term memory network, which have not gained much attention in the literature. A number of long short-term memory networks are trained to predict the actions of the best response sequences. The trained networks are used to introduce a total of 24 new IPD strategies which were shown to successfully win standard tournaments. From this research the following conclusions are made: there is not a single best strategy in the IPD for varying environments, however, there are properties associated with the strategies’ success distinct to different environments. These properties reinforce and contradict well established results. They include being nice, opening with cooperation, being a little envious, being complex, adapting to the environment and using longer memory when possible

2007 Abstract Booklet

Complete Schedule of Events for the 9th Annual Undergraduate Research Conference at Minnesota State University, Mankato

Coevolution in Complex Networks : An analysis of socio-natural interactions for wetlands management

Coevolution between natural and social systems comprises interaction, reciprocal dynamics and reciprocal adaptation. The notion derives primarily from evolutionary biology, but also from the study of complex systems. This dissertation aims to: “develop the means to assess the effects of different human interventions on the future coevolution of interacting natural and social systems.” The method that I develop is termed ‘topological network analysis’, highlighting my focus on the topology – number and pattern of interactions – of complex networks. A socio-natural network integrates interactions within and between a natural and a social system. Topological network analysis simulates and compares the effect of different human interventions on the network’s topology. It comprises four steps: 1. construction of a reference socio-natural network capturing the current situation for a given region; 2. specification of alternative development paths for the region; 3. translation of these paths into change in the network; and 4. comparison of the alternative paths according to their estimate impacts on the robustness of the network and so the stability of the system . This last step leads to management insights. Topological network analysis is illustrated by considering conversion of a stand of mangroves in the Philippines. The dissertation focuses on human intervention into ecosystem and on the potential for subsequent biodiversity loss. Topological network may be best applied to decision problems or management issues involving differential effects on species’ survival.Nijkamp, P. [Promotor]Opschoor, J.B. [Promotor

An Initial Framework Assessing the Safety of Complex Systems

Trabajo presentado en la Conference on Complex Systems, celebrada online del 7 al 11 de diciembre de 2020.Atmospheric blocking events, that is large-scale nearly stationary atmospheric pressure patterns, are often associated with extreme weather in the mid-latitudes, such as heat waves and cold spells which have significant consequences on ecosystems, human health and economy. The high impact of blocking events has motivated numerous studies. However, there is not yet a comprehensive theory explaining their onset, maintenance and decay and their numerical prediction remains a challenge. In recent years, a number of studies have successfully employed complex network descriptions of fluid transport to characterize dynamical patterns in geophysical flows. The aim of the current work is to investigate the potential of so called Lagrangian flow networks for the detection and perhaps forecasting of atmospheric blocking events. The network is constructed by associating nodes to regions of the atmosphere and establishing links based on the flux of material between these nodes during a given time interval. One can then use effective tools and metrics developed in the context of graph theory to explore the atmospheric flow properties. In particular, Ser-Giacomi et al. [1] showed how optimal paths in a Lagrangian flow network highlight distinctive circulation patterns associated with atmospheric blocking events. We extend these results by studying the behavior of selected network measures (such as degree, entropy and harmonic closeness centrality)at the onset of and during blocking situations, demonstrating their ability to trace the spatio-temporal characteristics of these events.This research was conducted as part of the CAFE (Climate Advanced Forecasting of sub-seasonal Extremes) Innovative Training Network which has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 813844

The medicalization of deviance in China

亞洲犯罪學學會Conference Theme: Asian Innovations in Criminology and Criminal JusticePart 5: Juvenile Delinquency and JusticeConrad and Schneider’s now classical work on the historical transformation of definitions of deviance from “badness” to “sickness” is relevant for the situation in China today, although with some modifications. The weakly founded medical/psychiatric profession and the strong political/ideological discourse in China leads to a strange combination of medicalization and moralization, even criminalization of deviance. The “sick” is often combined with the “bad”, and “sickness” is often seen as a secondary sign of “badness”. The pan-moralist tradition of ancient China seems to be closely combined with the Communist era’s strong belief in political-ideological correctness, and its strong belief in social engineering. It is interesting to note that my research on crime and deviance in China in the 1980s and 1990s seems to be confirmed by today’s discourse, although there are new moral panics and new forms of medical-moralistic definitions of deviance in China today. Still, the categories of deviance are very much socially constructed entities closely related to the moral-political order of present day China. I will use three cases to underline my argument. First, the type of deviance I call “majority deviance”, related to the case of the prejudice and dangers associated with the only-child. My second example has to do with what I term the “wayward girl” and the moral panics concerning so-called zaolian – or “premature love” among young girls. The third example is the new panic surrounding “internet addiction disorder” or IAD. While the “disco” and the “dance hall” were the sites of disorder in the 1980s and 90s, the wangba – or “internet bar” is now seen as the most dangerous site of crime and deviance.postprin