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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Gi Hyun Lim Il Hong Suh |
| Copyright Year | 2008 |
| Description | Author affiliation: Coll. of Inf. & Commun., Hanyang Univ., Seoul (Gi Hyun Lim) |
| Abstract | Semantic knowledge especially for robots is often used as a form of knowledge representation which includes ontological knowledge to support description logics and rule language. However, it is difficult to design rules which provide some goal-associated context, object and space (COS)-action complexes to be used to infer alternative attempts for success of a goal, when current attempt is not satisfactory. To cope with such a difficulty, we propose a novel weighted action-coupled semantic network (wASN) which is used to recursively update and infer goal-associated COS-action complexes. To be specific, as in the semantic networks, wASN is a graph consisting of nodes and edges, respectively, to represent concepts-such as perception, object, space and context, and to represent semantic relation between the concepts. And, those concepts are designed to be all coupled with their associated actions. On the other hand, as in neural networks, our proposed wASN is designed to have weighted values of the connections among semantic nodes. And those weighted values are summed at each node, and are used to adopt a node by ldquowinner-takes-allrdquo activation strategy. It is shown that wASN is useful to recursively get COS-action complexes for a specific task to find objects which are partially occluded or unobservable. |
| Starting Page | 2035 |
| Ending Page | 2040 |
| File Size | 1967120 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781424420575 |
| DOI | 10.1109/IROS.2008.4650928 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2008-09-22 |
| Publisher Place | France |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Robots Ontologies Robot sensing systems Robot kinematics Context modeling Artificial neural networks Knowledge engineering |
| Content Type | Text |
| Resource Type | Article |
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