Türkiye’de Dış Borç Sorunu ve 1980 Sonrası Boyutları

A novel technique is presented to construct sparse regression models based on the orthogonal least square method with boosting. This technique tunes the mean vector and diagonal covariance matrix of individual regressor by incrementally minimizing the training mean square error. A weighted optimization method is developed based on boosting to append regressors one by one in an orthogonal forward selection procedure. Experimental results obtained using this technique demonstrate that it offers a viable alternative to the existing state-of-art kernel modeling methods for constructing parsimonious regression models

Single-player monte-carlo tree search

Abstract. Classical methods such as A * and IDA * are a popular and successful choice for one-player games. However, they fail without an accurate admissible evaluation function. In this paper we investigate whether Monte-Carlo Tree Search (MCTS) is an interesting alternative for one-player games where A * and IDA * methods do not perform well. Therefore, we propose a new MCTS variant, called Single-Player Monte-Carlo Tree Search (SP-MCTS). The selection and backpropagation strategy in SP-MCTS are different from standard MCTS. Moreover, SP-MCTS makes use of a straightforward Meta-Search extension. We tested the method on the puzzle SameGame. It turned out that our SP-MCTS program gained the highest score so far on the standardized test set.

Planning for Interactions among Autonomous Agents

Abstract. AI planning research has traditionally focused on offline planning for static single-agent environments. In environments where an agent needs to plan its interactions with other autonomous agents, planning is much more complicated, because the actions of the other agents can induce a combinatorial explosion in the number of contingencies that the planner will need to consider. This paper discusses several ways to alleviate the combinatorial explosion, and illustrates their use in several different kinds of multi-agent planning domains.

A Day in the Life of a Male College Athlete: A Public Perception and Qualitative Campus Investigation

Perceptual confirmation paradigm (PCP) rooted in social psychology, can be implemented to frame sport science research questions (Stone, Perry, & Darley, 1997). Public perception of college athletes\u27 lives has been scarcely investigated in the sport sciences (Keels, 2005) using the PCP to prime stereotypes. The purpose of this study was to prime stereotypes about a day in the life of a college athlete by using qualitative inquiry to assess college students\u27 (N = 87) perceptions. Participants provided written responses about a day in the life of a college athlete. Two different college athlete targets were used Tyrone Walker (n = 44) and Erik Walker (n = 43). Four major themes and one minor theme emerged which are descriptive of the participants\u27 perceptions. Findings were related to the leadership responsibilities of sport management practitioners in higher education. Future research inquiries and relevant suggestions were articulated for sport management scholars in the 21st century. © 2009 Human Kinetics, Inc