Name
Abstract | ||
|---|---|---|
We present a novel approach to embodied learning of qualitative models. We introduce, algorithm STRUDEL that enables an autonomous robot to discover new concepts by performing experiments in its environment. The robot collects data about its actions and its observations of the environment. Prom the obtained data, the robot lean is qualitative descriptive models of the effects that its actions have in the environment. Models are learned using inductive logic programming. We describe two experiments with a humanoid robot Nao in which Nao learns descriptive qualitative models which contain what can be interpreted as simple definitions of the concepts of movability and stability. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1142/S0218488511007088 | INTERNATIONAL JOURNAL OF UNCERTAINTY FUZZINESS AND KNOWLEDGE-BASED SYSTEMS |
Keywords | Field | DocType |
Cognitive robotics, inductive logic programming, predicate invention, qualitative modeling, symbolic modeling | Cognitive robotics,Inductive logic programming,Embodied learning,Computer science,Embodied cognition,Artificial intelligence,Robot,Autonomous robot,Machine learning,Humanoid robot | Journal |
Volume | Issue | ISSN |
19 | 3 | 0218-4885 |
Citations | PageRank | References |
3 | 0.41 | 9 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Aljaz Kosmerlj | 1 | 5 | 1.13 |
| Ivan Bratko | 2 | 1526 | 405.03 |
| Jure Zabkar | 3 | 18 | 4.36 |