The concept of modeling multiple complex adaptive systems (CAS) as if they were voting processes proposes that an Error Resilient Data Fusion (ERDF) method can help to mitigate the effects of emergent properties in CAS system-of-systems (SoS). The property of emergence in a CAS composed of multiple, multi-modal sensors poses specific problems for fusion processes due to the difficulty in predicting and accounting for sensor performance under disparate environmental conditions. This paper compares the voting and Choquet integral fusion methods in the context of a multi-modal sensor ERDF SoS.

It is now time to begin the study of personal genome services based on the interdisciplinary theories and technologies of genomics and artificial intelligence (AI). Although recently much attention has been given to personal genome services for realizing personal medicine, little systematic research has been done on their communication and computational aspects for intelligent wellness service in AI communities. We believe that the intelligent personal genome services of the future need to include an understanding of how the knowledge of genetic risk influences people's behavior. This paper proposes the concept of MyFinder, a new framework for realizing an intimate personal genome service with AI technologies. This paper also describes the grand challenge problems of personal genome services that the AI and genomics communities should tackle jointly.

Among the issues faced by an intelligent agent, central is that of reconciling the, often contradictory, pieces of knowledge — be those given, learned, or sensed — at its disposal. This problem, known as knowledge qualification, requires that pieces of knowledge deemed reliable in some context be given preference over the others. These preferences are typically viewed as encodings of reasoning patterns; so, the frame axiom can be encoded as a preference of persistence over spontaneous change. Qualification, then, results by the principled application of these preferences. We illustrate how this can be naturally done through argumentation, by uniformly treating object-level knowledge and reasoning patterns alike as arguments that can be defeated by other stronger ones. We formulate an argumentation framework for Reasoning about Actions and Change that gives a semantics for Action Theories that include a State Default Theory. Due to their explicit encoding as preferences, reasoning patterns can be adapted, when and if needed, by a domain designer to suit a specific application domain. Furthermore, the reasoning patterns can be defeated in lieu of stronger external evidence, allowing, for instance, the frame axiom to be overridden when unexpected sensory information suggests that spontaneous change may have broken persistence in a particular situation.

The classic dualism offered in Descartes' The English language is rich with words and phrases with Meditations on First Philosophy (1641) views a person as meaning that is grounded in our commonsense theories of having both a physical body and a nonphysical mind.

An intelligent system of the future should make its user feel comfortable, which is impossible without understanding context they coexist in. However, our past research did not treat language information as a part of the context a robot works in, and data about reasons why the user had made his decisions was not obtained. Therefore, we decided to utilize the Web as a knowledge source to discover context information that could suggest a robot's behavior when it acquires verbal information from its user or users. By comparing user utterances (blogs, Twitter or Facebook entries, not direct orders) with other people's written experiences (mostly blogs), a system can judge whether it is a situation in which the robot can perform or improve its performance. In this paper we introduce several methods that can be applied to a simple floor-cleaning robot. We describe basic experiments showing that text processing is helpful when dealing with multiple users who are not willing to give rich feedback. For example, we describe a method for finding usual reasons for cleaning on the Web by using Okapi BM25 to extract feature words from sentences retrieved by the query word "cleaning". Then, we introduce our ideas for dealing with conflicts of interest in multiuser environments and possible methods for avoiding such conflicts by achieving better situation understanding. Also, an emotion recognizer for guessing user needs and moods and a method to calculate situation naturalness are described.

Within the context of human/multi-robot teams, the "help me help you" paradigm offers different opportunities. A team of robots can help a human operator accomplish a goal, and a human operator can help a team of robots accomplish the same, or a different, goal. Two scenarios are examined here. First, a team of robots helps a human operator search a remote facility by recognizing objects of interest. Second, the human operator helps the robots improve their position (localization) information by providing quality control feedback.

Spoken language is an important and natural way for people to communicate with computers. Nonetheless, habitable, reliable, and efficient human-machine dialogue remains difficult to achieve. This paper describes a multi-threaded semi-synchronous architecture for spoken dialogue systems. The focus here is on its utterance interpretation module. Unlike most architectures for spoken dialogue systems, this new one is designed to be robust to noisy speech recognition through earlier reliance on context, a mixture of rationales for interpretation, and fine-grained use of confidence measures. We report here on a pilot study that demonstrates its robust understanding of users’ objectives, and we compare it with our earlier spoken dialogue system implemented in a traditional pipeline architecture. Substantial improvements appear at all tested levels of recognizer performance.

Considering few treatments are available to slow or stop neurodegenerative disorders, such as Alzheimer’s disease and related dementias (ADRD), modifying lifestyle factors to prevent disease onset are recommended. The Voice, Activity, and Location Monitoring system for Alzheimer’s disease (VALMA) is a novel ambulatory sensor system designed to capture natural behaviours across multiple domains to profile lifestyle risk factors related to ADRD. Objective measures of physical activity and sleep are provided by lower limb accelerometry. Audio and GPS location records provide verbal and mobility activity, respectively. Based on a familiar smartphone package, data collection with the system has proven to be feasible in community-dwelling older adults. Objective assessments of everyday activity will impact diagnosis of disease and design of exercise, sleep, and social interventions to prevent and/or slow disease progression.

Most of the developing countries are re-inventing the wheel in their efforts to launch egovernment initiatives — especially in the areas of healthcare, education, economic development, supply chains for food distribution, and emergency services. A Computer Aided Strategic Planner, part of the UN eNabler Toolset, has been developed to quickly and effectively produce detailed strategic plans for a wide range of egovernment services based on best practices and standards. The generated plan is highly customized for the type of service as well as the country/region by using the latest thinking in AI, ontologies, and patterns. The Planner, available through the UN-GAID initiative, can be and has been used very effectively to educate as well as assist the government officials of developing countries to accelerate progress in crucial areas.

The increasing agility of business requires an accelerated adaptation of organizations to continuously changing conditions. Individual and organizational learning are prominent means to achieve this. Hereby learning is always accompanied by the development of knowledge artifacts. For the entire of learning and artifact development the term knowledge maturing has been introduced recently, which focuses on these three manifestations of knowledge: cognifacts, sociofacts, and artifacts. In this paper we will focus on sociofacts as the subject-bound knowledge manifestation of social actions. Sociofacts are rooted in respective cognifacts play an independent role due to their binding to collective actions and subjects. These are particularly difficult to grasp but play a decisive role for the performance of organizations and the collaboration in there.The presented paper approaches the notion of sociofacts, discusses them on a theoretical level and establishes a first formal notation for sociofacts. We use the case of a merger between two companies to describe the advantages of sociofact analysis for such process. Some sociofact related problems during a merger are described and possible solutions are presented. We identify technical approaches for seizing sociofacts from tool-mediated social interaction and discuss open question for future research.