Best Response Games on Regular Graphs

With the growth of the internet it is becoming increasingly important to understand how the behaviour of players is affected by the topology of the network interconnecting them. Many models which involve networks of interacting players have been proposed and best response games are amongst the simplest. In best response games each vertex simultaneously updates to employ the best response to their current surroundings. We concentrate upon trying to understand the dynamics of best response games on regular graphs with many strategies. When more than two strategies are present highly complex dynamics can ensue. We focus upon trying to understand exactly how best response games on regular graphs sample from the space of possible cellular automata. To understand this issue we investigate convex divisions in high dimensional space and we prove that almost every division of $k-1$ dimensional space into $k$ convex regions includes a single point where all regions meet. We then find connections between the convex geometry of best response games and the theory of alternating circuits on graphs. Exploiting these unexpected connections allows us to gain an interesting answer to our question of when cellular automata are best response games

Complex Networks from Simple Rewrite Systems

Complex networks are all around us, and they can be generated by simple mechanisms. Understanding what kinds of networks can be produced by following simple rules is therefore of great importance. We investigate this issue by studying the dynamics of extremely simple systems where are `writer' moves around a network, and modifies it in a way that depends upon the writer's surroundings. Each vertex in the network has three edges incident upon it, which are colored red, blue and green. This edge coloring is done to provide a way for the writer to orient its movement. We explore the dynamics of a space of 3888 of these `colored trinet automata' systems. We find a large variety of behaviour, ranging from the very simple to the very complex. We also discover simple rules that generate forms which are remarkably similar to a wide range of natural objects. We study our systems using simulations (with appropriate visualization techniques) and analyze selected rules mathematically. We arrive at an empirical classification scheme which reveals a lot about the kinds of dynamics and networks that can be generated by these systems

Chris Cannings: A Life in Games

Chris Cannings was one of the pioneers of evolutionary game theory. His early work was inspired by the formulations of John Maynard Smith, Geoff Parker and Geoff Price; Chris recognized the need for a strong mathematical foundation both to validate stated results and to give a basis for extensions of the models. He was responsible for fundamental results on matrix games, as well as much of the theory of the important war of attrition game, patterns of evolutionarily stable strategies, multiplayer games and games on networks. In this paper we describe his work, key insights and their influence on research by others in this increasingly important field. Chris made substantial contributions to other areas such as population genetics and segregation analysis, but it was to games that he always returned. This review is written by three of his students from different stages of his career

Intrabody Gene Therapy Ameliorates Motor, Cognitive, and Neuropathological Symptoms in Multiple Mouse Models of Huntington's Disease

Huntington's disease (HD) is an autosomal dominant neurodegenerative disease resulting from the expansion of a glutamine repeat in the huntingtin (Htt) protein. Current therapies are directed at managing symptoms such as chorea and psychiatric disturbances. In an effort to develop a therapy directed at disease prevention we investigated the utility of highly specific, anti-Htt intracellular antibodies (intrabodies). We previously showed that V_(L)12.3, an intrabody recognizing the N terminus of Htt, and Happ1, an intrabody recognizing the proline-rich domain of Htt, both reduce mHtt-induced toxicity and aggregation in cell culture and brain slice models of HD. Due to the different mechanisms of action of these two intrabodies, we then tested both in the brains of five mouse models of HD using a chimeric adeno-associated virus 2/1 (AAV2/1) vector with a modified CMV enhancer/chicken β-actin promoter. V_(L)12.3 treatment, while beneficial in a lentiviral model of HD, has no effect on the YAC128 HD model and actually increases severity of phenotype and mortality in the R6/2 HD model. In contrast, Happ1 treatment confers significant beneficial effects in a variety of assays of motor and cognitive deficits. Happ1 also strongly ameliorates the neuropathology found in the lentiviral, R6/2, N171-82Q, YAC128, and BACHD models of HD. Moreover, Happ1 significantly prolongs the life span of N171-82Q mice. These results indicate that increasing the turnover of mHtt using AAV-Happ1 gene therapy represents a highly specific and effective treatment in diverse mouse models of HD

Oregon’s Governor Deserved Better

Last Friday, after a week of intense scrutiny and speculation, the Democratic Governor of Oregon, John Kitzhaber announced his resignation over his alleged conflict of interest with his fiancée’s use of her government connections to further her private business. The University of Oregon’s Priscilla Southwell argues that commentators have failed to understand just how close-knit Oregon’s political and policy communities are. She writes that given Governor Kitzhaber’s 37 years of state service, he deserved the due process of the law and not a media trial and ‘execution’