Marsa-Maestre, Ivan (Universidad de Alcala) | Lopez-Carmona, Miguel A. (Universidad de Alcala) | Velasco, Juan R. (Universidad de Alcala) | Ito, Takayuki (MIT Sloan School of Management) | Klein, Mark (MIT Sloan School of Management) | Fujita, Katsuhide (Nagoya Institute of Technology)
Negotiation scenarios involving nonlinear utility functions are specially challenging, because traditional negotiation mechanisms cannot be applied. Even mechanisms designed and proven useful for nonlinear utility spaces may fail if the utility space is highly nonlinear. For example, although both contract sampling and constraint sampling have been successfully used in auction based negotiations with constraint-based utility spaces, they tend to fail in highly nonlinear utility scenarios. In this paper, we will show that the performance of these approaches decrease drastically in highly nonlinear utility scenarios, and propose a mechanism which balances utility and deal probability for the bidding and deal identification processes. The experiments show that the proposed mechanisms yield better results than the previous approaches in highly nonlinear negotiation scenarios.
The World Health Organization (WHO) has said it is preparing for "the worst case scenario" as it deals with a recent outbreak of the deadly Ebola virus in the Democratic Republic of Congo from spreading any further. The health agency will begin sending vaccines "as quickly as possible" to the northwestern town of Bikoro and surrounding areas, where 18 people are suspected to have died as a result of the virus in recent weeks, WHO Director-General Tedros Adhanom Ghebreyesus said in a Twitter post on Friday. Yesterday I spoke by phone with the Minister of Health of the Democratic Republic of the Congo @OlyIlunga to discuss the #Ebola response in #DRC. We agreed to ship vaccines as quickly as possible so they can be used to save lives. A team of WHO experts, alongside regional health officials and staff from international medical charity Doctors Without Borders (known by its French initials, MSF), are working in Bikoro as part of a coordinated medical response to the crisis.
Programming-by-Example approaches allow users to transform data by simply entering the target data. However, current methods do not scale well to complicated examples, where there are many examples or the examples are long.In this paper, we present an approach that exploits the fact that users iteratively provide examples.It reuses the previous subprograms to improve the efficiency in generating new programs.We evaluated the approach with a variety of transformation scenarios.The results show that the approach significantly reduces the time used to generate the transformation programs, especially in complicated scenarios.
With the avalanche of electronic text collections descending from all over the web, new forms of document processing that facilitate automatic extraction of useful information from texts are required. One approach for understanding the key aspects of a document or of a set of documents is to analyze the events in the document(s) and to automatically find scenarios of related events.