Murray's History of Chess is regarded as the most authoritative and most comprehensive history of the game. Murray's aim is threefold: to present as complete a record as is possible of the varieties of chess that exist or have existed in different parts of the world; to investigate the ultimate origin of these games and the circumstances of the invention of chess; and to trace the development of the modern European game from the first appearance of its ancestor, the Indian chaturanga, in the beginning of the 7th century. The first part of the book describes the history of the Asiatic varieties of chess, the Arabic and Persian literature on chess, and the theory and practice of the game of shatranj. The second part is concerned with chess in Europe in the Middle Ages, its role in literature and in the moralities, and with medieval chess problems, leading up to the beginning of modern chess and the history of the modern game through to the 19th century.

This updated and reorganized Third Edition of this textbook takes a workbook-style approach that encourages an active approach to learning statistics. Carefully placed reading questions throughout each chapter allow students to apply their knowledge right away, while in-depth activities based on current behavioral science scenarios, each with problem sets and quiz questions, give students the opportunity to assess their understanding of concepts while reading detailed explanations of more complex statistical concepts. Additional practice problems further solidify student learning. Most activities are self-correcting, so if a concept is misunderstood, this misunderstanding is corrected early in the learning process. After working through each chapter, students are far more likely to understand the material than when they only read the material.

After retiring from a successful law practice, Silverman enrolled in graduate school and at age 74 received a master's degree.

As has been pointed out by several industrial game AI developers the lack of behavioral modularity across games and in-game tasks is detrimental for the development of high quality AI [605, 171]. An increasingly popular method for ad-hoc behavior authoring that eliminates the modularity limitations of FSMs and BTs is the utility-based AI approach which can be used for the design of control and decision making systems in games [425, 557]. Following this approach, instances in the game get assigned a particular utility function that gives a value for the importance of the particular instance [10, 169]. For instance, the importance of an enemy being present at a particular distance or the importance of an agent’s health being low in this particular context. Given the set of all utilities available to an agent and all the options it has, utility-based AI decides which is the most important option it should consider at this moment [426]. The utility-based approach is grounded in the utility theory of economics and is based on utility function design. The approach is similar to the design of membership functions in a fuzzy set. A utility can measure anything from observable objective data (e.g., enemy health) to subjective notions such as emotions, mood and threat. The various utilities about possible actions or decisions can be aggregated into linear or non-linear formulas and guide the agent to take decisions based on the aggregated utility. The utility values can be checked every n frames of the game. So while FSMs and BTs would examine one decision at a time, utility-based AI architectures

What bearing do our histories--our influences, what we have done and what has happened to us--have on our responsibility for the actions we take or consider in the present? This is the question at the center of Alfred R. Mele's examination of moral responsibility, including the moral responsibility of manipulated agents. Departing from other scholars writing on free will and moral responsibility, Mele reflects on a wide range of thought experiments that feature agents who have been manipulated or designed in ways which directly affect their actions. Although such thought experiments are often used by philosophers to illustrate significant features of moral responsibility, little attention has been paid to ways in which various details make a difference. In Manipulated Agents, Mele addresses this gap, arguing that such vignettes have the potential to unlock an understanding of moral responsibility that takes an agent's history into account when assigning moral praise or blame. In his analysis of these thought experiments, Mele presents a highly accessible, compelling defense of a "history-sensitive" conception of moral responsibility that has implications for free will.