Challenges and Gaps in Reasoning Systems Clause Samples

Challenges and Gaps in Reasoning Systems. It is difficult to define milestones for the roadmap of reasoning technologies for the upcoming decades, because, albeit significant progress can be expected, many trends are of a gradual nature. One of these evident trends concerns the hardware that “embodies” reasoning software. The ever on-going process of miniaturization of microchips with an exponentially increasing processing capacity (compare “▇▇▇▇▇’▇ law”)allows processing bigger volumina of data in smaller devices. Less expensive and smaller processing hardware will lead—at least in a long term—to the moment when awareness and intelligence will be present in most devices at home. Furthermore, following concepts of Ambient Intelligence (AmI), there will be more sensors in the environment whose data requires (and allows) additional processing. Many sensor devices will perform pre-processing on their boards and provide higher level reasoning levels in a distributed reasoning system data of a higher quality. Mobile devices (e.g. smartphones and tablets) will perform reasoning tasks that nowadays only PCs are able to perform. Their connectedness (see the section about “Communicating”) and their processing power allows reasoning systems to process data almost everywhere on mobile (i.e. wearable) devices. A challenge here is to design and to implement efficient software algorithms that can run on mobile devices with their limited energy. Another trend is the increasing distribution of reasoning through the storage and processing of data in the cloud. It is a challenging to design smart Internet (software) agents that find information related to the context of end-users in the (semantic) web, which is machine interpretable, and their interfaces to human readable Internet as most of the readers know it today. In summary of the last paragraphs, reasoning in AAL is expected to happen not for much longer on relatively powerful computers that were installed in the flats of users in some research projects in the past, in the future, but distributed on the sensors, in the environment, on mobile devices (smartphones and tablets) and in the cloud. A realistic goal for the mid and long term is to offer the end-users of different kind (older people, caregivers and nurses, service providers)better, user-friendly and reliable AAL Decision Support Systems (AALDSS) that are designed to coach the users while addressing also motivational and emotional aspects (instead of just prompting “you have to practice more sports”),...