Alle Publikationen
- <<
- <
- 1
2013
-
(2013) : Let the machines do. How intelligent is Artificial Intelligence?: 2013 36th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO): Opatija, Croatia: IEEE, S. 947-952
Abstract: “Intelligent” systems are present around us. Such machines are not only tools in our hands, they are able to make decisions and perform actions directly in the real world or in the artificial worlds of the internet. But even in the latter case, their decisions have consequences to our life. Many of them still act as “assistance systems”, leaving the final decision to the human user. The trend goes to more autonomy of the machines, even in critical situations when humans become overloaded by complexity. Additionally, humans are more and more willing to accept the proposals of the machines. But is this technique mature enough to guide or even to replace human decision-making? Especially, perception appears to be a hard problem for technical equipment. How accurate, how safe can decisions be in the case of incomplete and unreliable data? The paper gives some overview about recent developments in Artificial Intelligence and Robotics, their capabilities and serious problems from a general point of view.
2005
-
(2005): Active affective State detection and user assistance with dynamic bayesian networks. In: IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans 35 (1), S. 93-105. DOI: 10.1109/TSMCA.2004.838454
DOI: https://doi.org/10.1109/TSMCA.2004.838454 Abstract: With the rapid development of pervasive and ubiquitous computing applications, intelligent user-assistance systems face challenges of ambiguous, uncertain, and multimodal sensory observations, user’s changing state, and various constraints on available resources and costs in making decisions. We introduce a new probabilistic framework based on the dynamic Bayesian networks (DBNs) to dynamically model and recognize user’s affective states and to provide the appropriate assistance in order to keep user in a productive state. We incorporate an active sensing mechanism into the DBN framework to perform purposive and sufficing information integration in order to infer user’s affective state and to provide correct assistance in a timely and efficient manner. Experiments involving both synthetic and real data demonstrate the feasibility of the proposed framework as well as the effectiveness of the proposed active sensing strategy.
Keywords: active affective state detection, active fusion, active sensing mechanism, affective state detection, Angemessen(heit) (von Technik), Bayesian methods, Bayesian networks (BNs), belief networks, Context modeling, Costs, dynamic Bayesian networks, Face detection, ieee xplore, information integration, Information theory, Intelligent networks, Intelligent sensors, Intelligent Systems, intelligent user assistance system, probabilistic framework, sensor fusion, Systems engineering, theory, Ubiquitous computing, user assistance, user interfaces
- <<
- <
- 1