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Riveting real-life accounts of heroism from Medal of Honor recipients, including Clinton Romesha (author of Red Platoon: A True Story of American Valor) and exceptional civilians like schoolteacher Jencie Fagan How does an ordinary person become a hero? It happens in a split second, a moment of focus and clarity, when a choice is made. Here are the gripping accounts of Medal of Honor recipients who demonstrated guts and selflessness on the battlefield and confronted life-threatening danger to make a difference. There are the stories of George Sakato and Vernon Baker both of whom overcame racial discrimination to enlist in the army during World War II (Sakato was a second-generation Japanese American, Baker an African American) and went on to prove that heroes come in all colors and Clint Romesha, who led his outnumbered fellow soldiers against a determined enemy to prevent the Taliban from taking over a remote U.S. Army outpost in Afghanistan. Also included are civilians who have been honored by the Congressional Medal of Honor Foundation for outstanding acts of bravery in crisis situations, from a school shooting to the 9/11 attacks on the World Trade Center. Adding depth and context are illuminating essays on the combat experience and its aftermath, covering topics such as overcoming fear; a mother mourning the loss of her son; and surviving hell as a prisoner of war."
Answer set programming (ASP) is a declarative language tailored towards solving combinatorial optimization problems. It has been successfully applied to e.g. planning problems, configuration and verification of software, diagnosis and database repairs. However, ASP is not directly suitable for modeling problems with continuous domains. Such problems occur naturally in diverse fields such as the design of gas and electricity networks, computer vision and investment portfolios. To overcome this problem we study FASP, a combination of ASP with fuzzy logic -- a class of manyvalued logics that can handle continuity. We specifically focus on the following issues: 1. An important question when modeling continuous optimization problems is how we should handle overconstrained problems, i.e. problems that have no solutions. In many cases we can opt to accept an imperfect solution, i.e. a solution that does not satisfy all the stated rules (constraints). However, this leads to the question: what imperfect solutions should we choose? We investigate this question and improve upon the state-of-the-art by proposing an approach based on aggregation functions. 2. Users of a programming language often want a rich language that is easy to model in. However, implementers and theoreticians prefer a small language that is easy to implement and reason about. We create a bridge between these two desires by proposing a small core language for FASP and by showing that this language is capable of expressing many of its common extensions such as constraints, monotonically decreasing functions, aggregators, S-implicators and classical negation. 3. A well-known technique for solving ASP consists of translating a program P to a propositional theory whose models exactly correspond to the answer sets of P. We show how this technique can be generalized to FASP, paving the way to implement efficient fuzzy answer set solvers that can take advantage of existing fuzzy reasoners.
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