Analysis of game playing agents with fingerprints

Evolutionary computation (EC) can create a vast number of strategies for playing simple games in a short time. Analysis of these strategies is typically more time-consuming than their production. As a result, analysis of strategies produced by an EC system is often lacking or restricted to the extraction of superficial summary Statistics and Probability; This thesis presents a technique for extracting a functional signature from evolved agents that play games. This signature can be used as a visualization of agent behavior in games with two moves and also provides a numerical target for clustering and other forms of automatic analysis. The fingerprint can be used to induce a similarity measure on the space of game strategies. This thesis develops fingerprints in the context of the iterated prisoner\u27s dilemma; we note that they can be computed for any two player simultaneous game with a finite set of moves. When using a clustering algorithm, the results are strongly influenced by the choice of the measure used to find the distance between or to compare the similarity of the data being clustered. The Euclidean metric, for example, rates a convex polytope as the most compact type of object and builds clusters that are contained in compact polytopes. Presented here is a general method, called multi-clustering, that compensates for the intrinsic shape of a metric or similarity measure. The method is tested on synthetic data sets that are natural for the Euclidean metric and on data sets designed to defeat k-means clustering with the Euclidean metric. Multi-clustering successfully discovers the designed cluster structure of all the synthetic data sets used with a minimum of parameter tuning. We then use multi-clustering and filtration on fingerprint data. Cellular representation is the practice of evolving a set of instructions for constructing a desired structure. This thesis presents a cellular encoding for finite state machines and specializes it to play the iterated prisoner\u27s dilemma. The impact on the character and behavior of finite state agents of using the cellular representation is investigated. For the cellular representation resented a statistically significant drop in the level of cooperation is found. Other differences in the character of the automaton generated with a direct and cellular representation are reported

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

Information system's project management and the phenomenon of trust.

The aim of this research was to investigate how the continual low success rate of IS projects could be improved through an evaluation of success and failure factors. A literature review revealed a comprehensive but uncoordinated history of research into the identification of the critical factors. This proved to be inconclusive, but did indicate that project management contributed more to the failures than the technology. A model for expressing the complexity of IS project environments is proposed to aid project teams with their strategy. Also, the criteria for measuring success of both project managemenat nd IS projects has been extended. Although many disciplines had considered trust as a success factor, this was missing within the domain of project management. To examine the effect of trust in an IS project environment a game termed Project Paradox was designed and run. A lack of trust was found to be compounded by conflicting objectives inherent within IS projects. It is recommended that the issues relating to trust should be considered and managed as an integral part of a risk analysis. To enable this to be realised in practice a framework for a Trust Audit is proposed. The thesis concludes with a number of research initiatives aimed at improving the success rate of IS projects

Information system's project management and the phenomenon of trust

The aim of this research was to investigate how the continual low success rate of IS projects could be improved through an evaluation of success and failure factors. A literature review revealed a comprehensive but uncoordinated history of research into the identification of the critical factors. This proved to be inconclusive, but did indicate that project management contributed more to the failures than the technology. A model for expressing the complexity of IS project environments is proposed to aid project teams with their strategy. Also, the criteria for measuring success of both project managemenat nd IS projects has been extended. Although many disciplines had considered trust as a success factor, this was missing within the domain of project management. To examine the effect of trust in an IS project environment a game termed Project Paradox was designed and run. A lack of trust was found to be compounded by conflicting objectives inherent within IS projects. It is recommended that the issues relating to trust should be considered and managed as an integral part of a risk analysis. To enable this to be realised in practice a framework for a Trust Audit is proposed. The thesis concludes with a number of research initiatives aimed at improving the success rate of IS projects.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Information system's project management and the phenomenon of trust

The aim of this research was to investigate how the continual low success rate of IS projects could be improved through an evaluation of success and failure factors. A literature review revealed a comprehensive but uncoordinated history of research into the identification of the critical factors. This proved to be inconclusive, but did indicate that project management contributed more to the failures than the technology. A model for expressing the complexity of IS project environments is proposed to aid project teams with their strategy. Also, the criteria for measuring success of both project managemenat nd IS projects has been extended. Although many disciplines had considered trust as a success factor, this was missing within the domain of project management. To examine the effect of trust in an IS project environment a game termed Project Paradox was designed and run. A lack of trust was found to be compounded by conflicting objectives inherent within IS projects. It is recommended that the issues relating to trust should be considered and managed as an integral part of a risk analysis. To enable this to be realised in practice a framework for a Trust Audit is proposed. The thesis concludes with a number of research initiatives aimed at improving the success rate of IS projects.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Characterization of self-organization processes in complex networks

Programa Doutoral em Física (MAP-fis)A estrutura de interações sociais numa população é muitas vezes modelada através de uma rede complexa que representa os indivíduos e respetivas relações sociais. Estas estruturas são conhecidas por afetarem de forma fundamental os processos dinâmicos que suportam. A caracterização desse efeito é, no entanto, uma tarefa complicada pois o tratamento matemático destes sistemas requer o estudo de um espaço de estados de grande dimensão, limitando a aplicabilidade de abordagens analíticas e numéricas. Esta tese teve como objetivo desenvolver métodos, inspirados na Física Estatística dos Sistemas Fora do Equilíbrio, com o fim de caracterizar processos dinâmicos em redes complexas. Nesta tese demonstramos que a estrutura de uma população naturalmente induz a emergência de padrões de correlações entre indivíduos que partilham traços semelhantes, um fenómeno também identificado em estudos empíricos. Estes padrões de correlações são independentes do tipo de processo dinâmico considerado, do tipo de informação que se propaga sendo observados numa classe alargada de redes complexas. Mostramos também que propriedades como o clustering e a densidade de ligações da rede têm um papel fundamental nos padrões de correlações emergentes. Outra questão fundamental diz respeito à relação entre as dinâmicas local e a global em redes sociais. De facto, as redes sociais afetam de forma tão fundamental os processos dinâmicos que suportam que em muitas situações o comportamento coletivo observado não tem qualquer relação aparente com a dinâmica local na sua génese. Este é um problema comum a muitos sistemas complexos e tipicamente associado a fenómenos emergentes e de auto-organização. Neste trabalho esta questão é explorada no contexto do problema da Cooperação e no âmbito da Teoria de Jogos Evolutiva. Para esse fim introduzimos uma quantidade que é estimada numericamente e a que damos o nome de Average Gradient of Selection (AGOS). Esta quantidade, relaciona de forma efetiva as dinâmicas local e global, possibilitando a descrição do processo de auto-organização em populações estruturadas. Através do AGOS mostramos que quando as interações entre indivíduos são descritas através do Dilema do Prisioneiro, uma metáfora popular no estudo da cooperação, a dinâmica coletiva emergente é sensível à forma da rede de interações entre os indivíduos. Em particular, demonstramos que quando a rede é homogénea (heterogénea) no que respeita à distribuição de grau o Dilema do Prisioneiro é transformado numa dinâmica coletiva de coexistência (coordenação). Mostramos ainda que esta transformação depende da pressão de seleção (associada ao grau de determinismo no processo de decisão dos indivíduos) e de taxa de mutações (a adoção espontânea de um novo comportamento por parte de um individuo) consideradas. A relação entre estas duas varáveis pode também resultar em alterações de regimes dinâmicos cujo o resultado pode, em casos particulares, resultar no desfecho drástico para a evolução da cooperação. Finalmente, fazemos uso do AGOS para caracterizar a dinâmica evolutiva da cooperação no caso em que a estrutura co-evolve. Demonstramos que na presença de uma estrutura social a dinâmica global é semelhante à de um jogo de coordenação entre N-pessoas, cujas características dependem de forma sensível das escalas de tempo relativas entre a evolução de comportamentos e a evolução da estrutura. Uma vez mais, a dinâmica global emergente contrasta com o Dilema do Prisioneiro que caracteriza as interações locais entre os indivíduos. Acreditamos que o AGOS, que pode ser facilmente aplicado no estudo de outros processos dinâmicos, proporciona uma contribuição significativa para o melhor entendimento de Sistemas Complexos, em particular aqueles em que as interações entre os elementos constituintes são bem definidos através uma rede complexa.The structure of social interactions in a population is often modeled by means of a complex network representing individuals and their social ties. These structures are known to fundamentally impact the processes they support. However, the characterization of how structure impacts a dynamical process is by no means an easy task. Indeed, the large configuration space spanned tends to limit the systematic applicability of numerical methods, while analytical treatments have failed to provide a good description of the system dynamics. The aim of this thesis was to develop methods inspired in the Statistical Physics of Systems far from equilibrium to characterize dynamical processes on complex networks. In this thesis we show how the structure of a population naturally induces the emergence of correlations between individuals that share similar traits, which is in accordance empirical evidence. These, so called, ’peer-influence” correlation patterns are independent of the type of dynamical process under consideration, the type of information being spread while being ubiquitous among a wide variety of network topologies. We have also find evidence that central to the ’peer-influence” patterns are topological features such as the clustering and the sparsity of the underlying network of interactions. Another fundamental problem concerns the relationship between local and global dynamics in social networks. Indeed, social networks affect in such a fundamental way the dynamics of the population they support that the collective, population-wide behavior that one observes often bears no relation to the individual processes it stems from. This is in fact a common problem among many Complex Systems typically associated with self-organization and emerging phenomena. Here we study this issue in the context of the problem of Cooperation and in the realm of Evolutionary Game Theory. To that end we introduce a numerically estimated mean-field quantity that we call the Average Gradient of Selection (AGOS). This quantity is able to effectively connect the local and global dynamics, providing a way to track the self-organization of cooperators and defectors in networked populations. With the AGOS we show that when individuals engage in a Prisoner’s Dilemma, a popular cooperation metaphor, the emerging collective dynamics depends on the shape of the underlying network of interactions. In particular, we show that degree homogeneous (heterogeneous) networks the Prisoner’s Dilemma is transformed into a collective coexistence (coordination) dynamics, contrasting with the defector dominance of the local dynamics. We further show that the extent to which these emergent phenomena are observed in structured populations is conditional on the selection pressure (the uncertainty associated with the decision making) and the rate of mutations (the spontaneously adoption of new behaviors by individuals) under consideration. Interestingly, the interplay between selection pressure and mutation rates can lead to drastic regime shifts in the evolution of cooperation. Finally, we make use of the AGOS to characterize the evolutionary dynamics of cooperation in the case of a co-evolving social structure. We demonstrate that in an adaptive social structure the population-wide dynamics resembles that of a N-person coordination game, whose characteristics depend sensitively on the relative time-scales between behavioral and network co-evolution. Once more, the resulting collective dynamics contrasts with the two-person Prisoner’s Dilemma that characterizes how individuals interact locally. We argue that the AGOS, which can be readily applied to other dynamical contexts and processes, provides a significant contribution to a better understanding of Complex Systems involving populations in which who interacts with whom is well-defined by a complex network

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