Learning plan applicability through active mental entities
- Universita di Brescia, Dipartimento di Elettronica per l'Automazione, Via Branze 38, 25123 Brescia (Italy)
This paper aims at laying down the foundations of a new approach to learning in autonomous mobile robots. It is based on the assumption that robots can be provided with built-in action plans and with mechanisms to modify and improve such plans. This requires that robots are equipped with some form of high-level reasoning capabilities. Therefore, the proposed learning technique is embedded in a novel distributed control architecture featuring an explicit model of robot's cognitive activity. In particular, cognitive activity is obtained by the interaction of active mental entities, such as intentions, persuasions and expectations. Learning capabilities are implemented starting from the interaction of such mental entities. The proposal is illustrated through an example concerning a robot in charge of reaching a target in an unknown environment cluttered with obstacles.
- OSTI ID:
- 21210406
- Journal Information:
- AIP Conference Proceedings, Vol. 465, Issue 1; Conference: CASYS'98: 2. international conference on computing anticipatory systems, Liege (Belgium), 10-14 Aug 1998; Other Information: DOI: 10.1063/1.58262; (c) 1999 American Institute of Physics; Country of input: International Atomic Energy Agency (IAEA); ISSN 0094-243X
- Country of Publication:
- United States
- Language:
- English
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