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While most activity recognition systems rely on data-driven approaches, the use of knowledge-driven techniques is gaining increasing interest. Research in this field has mainly concentrated on the use of ontologies to specify the semantics of activities, and ontological reasoning to recognize them based on context information. However, at the time of writing, the experimental evaluation of these techniques...
Trust and Belief are two very closely connected notions. Hence one would expect that any mechanism that guides the management of one can efficaciously guide the other. In fact, devices such as Dempster-Shafer's theory of evidence have been successfully used in the management of both. This paper looks at a different mechanism devised for inductive inferencing, namely Spohn's Ordinal Conditional Functions,...
This article re-visits the foundation concepts of Computational Intelligence in relation to the established field of Artificial Intelligence and describes an emerging data technology, Formal Concept Analysis, that can contribute to the topic. Technologies from Artificial Intelligence are briefly considered in relation to the need for improved knowledge representation and accessibility rather than...
This paper describes a method by which a massive multi-agent system can be influenced without resorting to micromanagement. This method could be utilized in the development of meta-reasoning components of individual agents. Agents in the system adopt the traits of their successful peers. The administrator guides this spread of traits through selectively injecting influential agents with modified traits...
This paper explores an improvement to activity recognition within a Smart Home environment using the Dempster-Shafer theory of evidence. This approach has the ability to be used to monitor human activities in addition to managing uncertainty in sensor based readings. A three layer lattice structure has been proposed, which can be used to combine the mass functions derived from sensors along with sensor...
In order for the intelligent assistant systems to provide users with timely and appropriate assistances, most of them focus on what is considered to be the "rational" aspect of the user behaviors. However, since human desire is the fundamental driving force of human behaviors, without including users' desires, the system cannot provide most appropriate responses. We propose a hierarchical...
Since 1960, lots of AI researchers work on intelligent and reactive architectures able to manage multiple events and act in the environment. This issue is also part of Robotics domain. A decision process must be implemented in the robot brain to accomplish the multimodal interaction with human in human environment. In this article, we present a semantic agents architecture giving the robot the ability...
Causal inference is one of the central capabilities of the natural intelligence that plays a crucial role in thought, perception, reasoning, and problem solving. This paper presents a set of cognitive models for causation analyses and causal inferences. The taxonomy and mathematical models of causations are created. The framework and properties of causal inferences are elaborated. Methodologies for...
We address the problem of estimating pose in a static image of a human performing an action that may involve interaction with scene objects. In such scenarios, pose can be estimated more accurately using the knowledge of scene objects. Previous approaches do not make use of such contextual information. We propose Pose Context trees to jointly model human pose and object which allows both accurate...
This paper presents KUCAS (Known User Continuous Authentication System), a work-in-progress security system, that has a continuous authentication mechanism of users/consumers. The KUCAS system makes use of environmental context information, users behavior analysis, the behavior theories of Skinner and the Mathematical Confidence of Dempster-Shafer Evidences Theory, that establishes trust levels to...
This paper explores a sensor fusion method within Smart Homes to be used to monitor human activities in addition to managing uncertainty in sensor based readings. A case study has shown that the Dempster-Shafer theory of evidence can incorporate the uncertainty derived from the sensor errors and the sensor context and infer the activity. The results from this work show that this method can detect...
Sensor network ubiquitous environments may generate a lot of data including heterogeneous `raw' sensor data, low-level feature and/or trend data and higher-level context and inferenced information. This paper considers the visualization of such large, heterogeneous and complex integrated information, especially for real-time deployments facilitating rapid understanding leading to decision making....
One of the challenges for ubiquitous intelligence computing is how to enable ubiquitous devices (u-devices) certain levels of intelligent/smart/autonomic/ processing capabilities. Due to their limited capacity and processing power, it is difficult to embed such capabilities into u-devices. The idea is to design an intelligence entity sharing pool in which an intelligence entity can be dynamically...
Collaborative design often meets together experts of different domains. Such groups need to share a context but often limited this one is often limited to few elements as common language, common tools and a same goal (the design process). Our goal is to developing a shared context to make compatible different experts' viewpoints. Making context explicit and shared supposes some explanatory capability...
This paper describes a research project that investigated the feasibility of using contextual reasoning to supervise the collaborative work of knowledge workers. In complex projects that require contributions from various experts but whose interaction may be limited to a web-based collaborative tool, proper management of the project is essential to ensure that the project objectives are met. This...
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