A predominant benefit of social living is the ability to share knowledge that cannot be gained through the information an individual accumulates based on its personal experience alone. Traditional computational models...A predominant benefit of social living is the ability to share knowledge that cannot be gained through the information an individual accumulates based on its personal experience alone. Traditional computational models have portrayed sharing knowledge through interactions among members of social groups via dyadic networks. Such models aim at understanding the percolation of information among individuals and groups to identify potential limitations to successful knowledge transfer. How- ever, because many real-world interactions are not solely pairwise, i.e., several group members may obtain information from one another simultaneously, it is necessary to understand more than dyadic communication and learning processes to capture their full complexity. We detail a modeling framework based on the simplicial set, a concept from algebraic topology, which allows elegant encapsulation of multi-agent interactions. Such a model system allows us to analyze how individual information within groups accumulates as the group＇s collective set of knowledge, which may be different than the simple union of individually contained information. Furthermore, the simplicial modeling approach we propose allows us to investigate how information accumulates via sub-group interactions, offering insight into complex aspects of multi-way communication systems. The fundamental change in modeling strategy we offer here allows us to move from portraying knowledge as a ＂token＂, passed from signaler to receiver, to portraying knowledge as a set of accumulating building blocks from which novel ideas can emerge. We provide an explanation of relevant mathematical concepts in a way that promotes accessibility to a general audience [Current Zoology 61 （1）： 114--127, 2015].展开更多
Some of the most important problems facing the United States and China, indeed facing our entire planet, require approaches that are fundamentally multidisciplinary in nature. Many of those require skills in computer ...Some of the most important problems facing the United States and China, indeed facing our entire planet, require approaches that are fundamentally multidisciplinary in nature. Many of those require skills in computer science （CS）, basic understanding of another discipline, and the ability to apply the skills in one discipline to the problems of another. Modern training in computer science needs to prepare students to work in other disciplines or to work on multidisciplinary problems. What do we do to prepare them for a multidisciplinary world when there are already too many things we want to teach them about computer science？ This paper describes successful examples of multidisciplinary education at the interface between CS and the biological sciences, as well as other examples involving CS and security, CS and sustainability, and CS and the social and economic sciences. It then discusses general principles for multidisciplinary education of computer scientists.展开更多
文摘A predominant benefit of social living is the ability to share knowledge that cannot be gained through the information an individual accumulates based on its personal experience alone. Traditional computational models have portrayed sharing knowledge through interactions among members of social groups via dyadic networks. Such models aim at understanding the percolation of information among individuals and groups to identify potential limitations to successful knowledge transfer. How- ever, because many real-world interactions are not solely pairwise, i.e., several group members may obtain information from one another simultaneously, it is necessary to understand more than dyadic communication and learning processes to capture their full complexity. We detail a modeling framework based on the simplicial set, a concept from algebraic topology, which allows elegant encapsulation of multi-agent interactions. Such a model system allows us to analyze how individual information within groups accumulates as the group＇s collective set of knowledge, which may be different than the simple union of individually contained information. Furthermore, the simplicial modeling approach we propose allows us to investigate how information accumulates via sub-group interactions, offering insight into complex aspects of multi-way communication systems. The fundamental change in modeling strategy we offer here allows us to move from portraying knowledge as a ＂token＂, passed from signaler to receiver, to portraying knowledge as a set of accumulating building blocks from which novel ideas can emerge. We provide an explanation of relevant mathematical concepts in a way that promotes accessibility to a general audience [Current Zoology 61 （1）： 114--127, 2015].
文摘Some of the most important problems facing the United States and China, indeed facing our entire planet, require approaches that are fundamentally multidisciplinary in nature. Many of those require skills in computer science （CS）, basic understanding of another discipline, and the ability to apply the skills in one discipline to the problems of another. Modern training in computer science needs to prepare students to work in other disciplines or to work on multidisciplinary problems. What do we do to prepare them for a multidisciplinary world when there are already too many things we want to teach them about computer science？ This paper describes successful examples of multidisciplinary education at the interface between CS and the biological sciences, as well as other examples involving CS and security, CS and sustainability, and CS and the social and economic sciences. It then discusses general principles for multidisciplinary education of computer scientists.
