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This book presents a historical overview of American Indian education and includes excerpts of government documents, court decisions, letters from commissioners of Indian affairs, and personal accounts. The book depicts the continuous efforts of White society to educate and assimilate Native Americans into the Euro-American culture. Chapters 1 and 2 characterize Indian education before European contact; describe traditional methods used to teach Indian children the rules, values, and world view of their society; contrast Indian education with that of early colonists; and describe early efforts to change the fundamental cultural orientation of the Indians. Other chapters cover the following topics: (1) treaty negotiations and violations; (2) mission education during the treaty years (1778-1871); (3) the religious school controversy (1869-1908); (4) tribally controlled education; (5) government boarding schools; (6) the 1928 Meriam Report that investigated all aspects of Indian affairs; (7) the Navajo-Hopi Rehabilitation Act of 1950; (8) the role of public schools; (9) the 1969 Kennedy Report that investigated the inequities of Indian education; (10) Indian self-determination and education; and (11) tribally controlled community colleges. Contains 51 references and an index. (LP)

The need for church-related colleges to assert their distinctive Christian agenda in the marketplace of higher education is explored. It is noted that the church-related college once followed notions that education should be value free and that academe should be divided into separate disciplines and specializations according to the Cartesian-Newtonian paradigm; this paradigm is critically analyzed. The book is divided into three parts. Part 1 describes what happened after World War II in American society, in the mainline Protestant denominations, and in higher education. It concludes with a critical analysis of the public university, the church-related college, and the relationship between the mainline Protestant denominations and American higher education. Part 2 prescribes a new raison d'etre for the church-related college by pointing it toward basic Christian tenets and toward the post-modern science paradigm, and by asking the church-related colleges to develop a new relationship with America's pluralistic society. Finally, in part 3, the book suggests ways in which church-related colleges can build their programs according to the principles posited, and argues that these colleges must seek to foster the growth of students as whole persons, focusing on their spiritual/moral as well as intellectual development. (GLR)

In common-interest spatial-dispersion games the agents’ common goal is to choose distinct locations. We experimentally investigate the role of cognition in such games and compare it with the role of cognition in spatial matching games. In our setup cognition matters because agents may be differentially aware of the dispersion opportunities that are created by the history of the game. We ask whether cognitive constraints limit the agents’ ability to achieve dispersion and, if there is dispersion, whether these constraints affect the mode by which agents achieve dispersion. Our main finding is that strategic interaction magnifies the role of cognitive constraints. Specifically, with cognitive constraints, pairs of agents fail to solve a dispersion problem that poses little or no problem for individual agents playing against themselves. When we remove the cognitive constraints in our design, pairs of agents solve the same problem just as well as individuals do. In addition, we find that when playing against themselves agents do not change the mode by which they solve the dispersion problem when our design removes the cognitive constraints. [ABSTRACT FROM AUTHOR]

While direct, model-free reinforcement learning often performs better than model-based approaches in practice, only the latter have yet supported theoretical guarantees for finite-sample convergence. A major difficulty in analyzing the direct approach in an online setting is the absence of a definitive exploration strategy. We extend the notion of admissibility to direct reinforcement learning and show that standard Q-learning with optimistic initial values and constant learning rate is admissible. The notion justifies the use of a greedy strategy that we believe performs very well in practice and holds theoretical significance in deriving finite-sample convergence for direct reinforcement learning. We present empirical evidence that supports our idea. [ABSTRACT FROM AUTHOR]

Incorporation of prior knowledge into the learning process can significantly improve low-sample classification accuracy. We show how to introduce prior knowledge into linear support vector machines in form of constraints on the rotation of the normal to the separating hyperplane. Such knowledge frequently arises naturally, e.g., as inhibitory and excitatory influences of input variables. We demonstrate that the generalization ability of rotationally-constrained classifiers is improved by analyzing their VC and fat-shattering dimensions. Interestingly, the analysis shows that large-margin classification framework justifies the use of stronger prior knowledge than the traditional VC framework. Empirical experiments with text categorization and political party affiliation prediction confirm the usefulness of rotational prior knowledge. [ABSTRACT FROM AUTHOR]

Coronary angiography delivers accurate information about the vessel topology and shape, but only limited data concerning the vessel cross-section. Intravascular ultrasound provides detailed information about the cross-sectional shape as well as the composition of vessel wall and plaque, but fails to consider the geometric relationships between adjacent images. In this paper, we present a new approach for combination of both methods to allow accurate assessment of coronary arteries regarding both longitudinal and cross-sectional dimensions. [ABSTRACT FROM AUTHOR]

Presents the author's views on the video recording "The Amazing Voyage of Gustave Flaubert and Raymond Roussel," directed by Steve Fagin. Description of the video; Factor that disallows the author to conjure the shifting and shuffling of the elements in the video; Rationale behind the belief that love should be included as a theme in the video.

Domain-independent classical planning is faced with serious difficulties. Many of these are traceable to some facet of the frame problem. Perfect knowledge of the planner's world and operators is impossible for most domains. With anything less, small unmodeled errors can result in large discrepancies between the expected and observed worlds. Such discrepancies may interfere with the achievement of a goal. Reactivity provides an extreme response. It allows only sensor information after an action is taken to judge the action's effects, and abandons projection altogether. There must be a vast space of possibilities between the extremes of classical planning and reactivity. This paper describes two called computable planning and permissive planning. Machine learning, in the form of Explanation-Based Learning, is used in computable planning to recognize deferrable goals, resulting in many of the benefits offered by reactivity but in a domain independent form. In permissive planning, machine learning techniques are used to refine plans through experience so that they become less sensitive to the necessarily approximate knowledge. [ABSTRACT FROM AUTHOR]