AUV fuzzy neural BDI
Liu Hai-bo , Gu Guo-chang , Shen Jing , Fu Yan
Journal of Marine Science and Application ›› 2005, Vol. 4 ›› Issue (3) : 37 -41.
AUV fuzzy neural BDI
The typical BDI (belief desire intention) model of agent is not efficiently computable and the strict logic expression is not easily applicable to the AUV (autonomous underwater vehicle) domain with uncertainties. In this paper, an AUV fuzzy neural BDI model is proposed. The model is a fuzzy neural network composed of five layers: input (beliefs and desires), fuzzification, commitment, fuzzy intention, and defuzzification layer. In the model, the fuzzy commitment rules and neural network are combined to form intentions from beliefs and desires. The model is demonstrated by solving PEG (pursuit-evasion game), and the simulation result is satisfactory.
autonomous underwater vehicle / fuzzy neural network / belief-desire-intention / pursuit-evasion game
| [1] |
|
| [2] |
SINGH M P, ASHER N M. Towards a formal theory of intentions [A]. Proceedings of the European Workshop JELIA-90 [C]. Amsterdam, 1991:472–486. |
| [3] |
RAO A S, GEORGEFF M P. An abstract architecture for rational agents [A]. Proceedings of the third International Conference on Principles of Knowledge Representation and Reasoning [C]. San Mateo, 1992:439–449. |
| [4] |
RAO A S, GEORGEFF M P. BDI agents: from theory to Practice [A]. Proceedings of the First International Conference on Multi-Agent Systems [C]. San Francisco, 1995: 312–319. |
| [5] |
|
| [6] |
|
| [7] |
|
| [8] |
|
| [9] |
XUAN P, LESSER V R. Handling uncertainty in multi-agent Commitments [R]. [S.L.]:University of Massachusetts Amherst, 1999. |
| [10] |
|
| [11] |
|
/
| 〈 |
|
〉 |