http://dl.gi.de/handle/20.500.12116/11111 2026-07-23T11:52:07Z 2026-07-23T11:52:07Z http://dl.gi.de/handle/20.500.12116/11424 2018-03-20T10:33:09Z 2014-01-01T00:00:00Z

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2014-01-01T00:00:00Z Sauer, Christian Severin Rintala, Lotta Roth-Berghofer, Thomas http://dl.gi.de/handle/20.500.12116/11429 2018-03-20T10:33:09Z 2014-01-01T00:00:00Z

Two-Phased Knowledge Formalisation for Hydrometallurgical Gold Ore Process Recommendation and Validation Sauer, Christian Severin; Rintala, Lotta; Roth-Berghofer, Thomas This paper describes an approach to externalising and formalising expert knowledge involved in the design and evaluation of hydrometallurgical process chains for gold ore treatment. The objective was to create a case-based reasoning application for recommending and validating a treatment process of gold ores. We describe a twofold approach. Formalising human expert knowledge about gold mining situations enables the retrieval of similar mining contexts and respective process chains, based on prospection data gathered from a potential gold mining site. Secondly, empirical knowledge on hydrometallurgical treatments is formalised. This enabled us to evaluate and, where needed, redesign the process chain that was recommended by the first aspect of our approach. The main problems with formalisation of knowledge in the domain of gold ore refinement are the diversity and the amount of parameters used in literature and by experts to describe a mining context. We demonstrate how similarity knowledge was used to formalise literature knowledge. The evaluation of data gathered from experiments with an initial prototype workflow recommender, Auric Adviser, provides promising results.

2014-01-01T00:00:00Z Hertzberg, Joachim Zhang, Jianwei Zhang, Liwei Rockel, Sebastian Neumann, Bernd Lehmann, Jos Dubba, Krishna S. R. Cohn, Anthony G. Saffiotti, Alessandro Pecora, Federico Mansouri, Masoumeh Konečný, Štefan Günther, Martin Stock, Sebastian Lopes, Luis Seabra Oliveira, Miguel Lim, Gi Hyun Kasaei, Hamidreza Mokhtari, Vahid Hotz, Lothar Bohlken, Wilfried http://dl.gi.de/handle/20.500.12116/11426 2018-03-20T10:33:09Z 2014-01-01T00:00:00Z

The RACE Project Hertzberg, Joachim; Zhang, Jianwei; Zhang, Liwei; Rockel, Sebastian; Neumann, Bernd; Lehmann, Jos; Dubba, Krishna S. R.; Cohn, Anthony G.; Saffiotti, Alessandro; Pecora, Federico; Mansouri, Masoumeh; Konečný, Štefan; Günther, Martin; Stock, Sebastian; Lopes, Luis Seabra; Oliveira, Miguel; Lim, Gi Hyun; Kasaei, Hamidreza; Mokhtari, Vahid; Hotz, Lothar; Bohlken, Wilfried This paper reports on the aims, the approach, and the results of the European project RACE. The project aim was to enhance the behavior of an autonomous robot by having the robot learn from conceptualized experiences of previous performance, based on initial models of the domain and its own actions in it. This paper introduces the general system architecture; it then sketches some results in detail regarding hybrid reasoning and planning used in RACE, and instances of learning from the experiences of real robot task execution. Enhancement of robot competence is operationalized in terms of performance quality and description length of the robot instructions, and such enhancement is shown to result from the RACE system.

2014-01-01T00:00:00Z Borth, Damian http://dl.gi.de/handle/20.500.12116/11434 2018-03-20T10:33:09Z 2014-01-01T00:00:00Z

Visual Learning of Semantic Concepts in Social Multimedia Borth, Damian

2014-01-01T00:00:00Z