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Argument Technology
Argument technology is a sub-field of collective intelligence and artificial intelligence that focuses on applying computational techniques to the creation, identification, analysis, navigation, evaluation and visualisation of arguments and debates. In the 1980s and 1990s, philosophical theories of arguments in general, and argumentation theory in particular, were leveraged to handle key computational challenges, such as modeling non-monotonic logic, non-monotonic and defeasible reasoning, defeasible reasoning and designing robust coordination protocols for multi-agent systems. At the same time, mechanisms for computing ''semantics'' of Argumentation frameworks were introduced as a way of providing a calculus of opposition for computing what it is reasonable to believe in the context of conflicting arguments. With these foundations in place, the area was kick-started by a workshop held in the Scottish Highlands in 2000, the result of which was a book coauthored by philosophers of ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Collective Intelligence
Collective intelligence (CI) is shared or group intelligence (GI) that Emergence, emerges from the collaboration, collective efforts, and competition of many individuals and appears in consensus decision making. The term appears in sociobiology, political science and in context of mass peer review and crowdsourcing applications. It may involve Consensus decision-making, consensus, social capital and formalisms such as voting systems, social media and other means of quantifying mass activity. Collective Intelligence quotient, IQ is a measure of collective intelligence, although it is often used interchangeably with the term collective intelligence. Collective intelligence has also been attributed to bacteria and animals. It can be understood as an emergent property from the synergies among: #data-information-knowledge #software-hardware #individuals (those with new insights as well as recognized authorities) that continually learn from feedback to produce just-in-time knowledge ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
