Identyfikatory
Warianty tytułu
System zachowania komunikacji w Systemie Wielo-agentowym z użyciem Impulsowej Sieci Neuronowej
Języki publikacji
Abstrakty
Present article discusses the position control system for autonomous agents on the test map. The main objectives for the system are: maintain best possible communication between the agents in the case of both limited local communication rang and disturbance in the communication. The control algorithm is based on Spiking Neural Network (SNN).
W przedstawionym artykule został omówiony system kontroli pozycji autonomicznych agentów w określonym terenie testowym. Podstawowym kryterium działania systemu jest zachowanie komunikacji pomiędzy agentami w sytuacji zarówno ograniczonego zasięgu łączności lokalnej jak i możliwych zakłóceń w łączności. Algorytm sterowania został oparty na Impulsowej Sieci Neuronowej.
Wydawca
Czasopismo
Rocznik
Tom
Strony
94--96
Opis fizyczny
Bibliogr. 19 poz., rys., wykr.
Twórcy
autor
- Politechnika Poznańska, Katedra Inżynierii Komputerowej
Bibliografia
- [1] Ferster D., Spruston N., Cracking the neuronal code, Science, 270 (1995), 756-757
- [2] Vreeken J., Spiking neural networks, an introduction, Adaptive Intelligence Laboratory, Institute of Information and Computing Science, Utrecht University
- [3] Gerstner W., Kempter R., Leo van Hemmen, Wagner J., Hebbian H., Bishop W., Learning of Pulse Timing in the Barn Owl Auditory System in Mass, Pulsed Neural Networks, MITpress, 1999
- [4] Floreano D., Mattiussi C., Evolution of spiking neural controllers for autonomous vision-based robots, Proceedings of the International Symposium on Evolutionary Robotics (ER-2001), 2001
- [5] Gerstner W., Kistler W., Spiking Neuron Models. Single Neurons, Populations, Plasticity, Cambridge University Press, Cambridge 2002
- [6] Colley M., de Souza G., Hagras H., Pounds-Cornish A., Clarke G., Callaghan V., Towards Developing Micro-scale Robots for Fluidic Enviroments Inaccassible
- [7] Ke Chen, Trends in neural computation, Berlin Heidelberg, Springer, 2007
- [8] Roth U., Walker M., Hilmann A., Klar H., Dynamic Path Planning with Spiking Neural Networks
- [9] Echegaray S., S. S., Wenbin L., Simulation of animal behavior using neural networks, Region 5 Conference, IEEE, 2006
- [10] Ichishita T., Fujii R.H., Performance Evaluation of a Temporal Sequence Learning Spiking Neural Network, Computer and Information Technology, 2007
- [11] Izhikevich E.M., Which Model to Use for Cortical Spiking Neurons?, IEEE Transactions on Neural Networks, Vol. 15, No. 5, September 2004
- [12] Bano N.F., Roppel T., Gokhale I., Use of Mobility Models for Communication in Collaborative Robotics, 42nd South Eastern Symposium on System Theory University of Texas at Tyler, TX, USA, March 7-9, 2010
- [13] Chao Y., Hongxia W., Developed Dijkstra Shortest Path Search Algorithm and Simulation, International Conference On Computer Design And Appliations (ICCDA 2010)
- [14] Fan D., Shi P., Improvement of Dijkstra’s Algorithm and Its Application in Route Planning, 2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2010)
- [15] Leung C., Al-Jumaily A., A Hybrid System for Multi-Agent Exploration, 25-29 July, 2004 Budapest, Hungary
- [16] Nizami M.S.H., AI-Arif S.M.M.R., Iftekharul Ferdous A.H.M., Riyadh Md. M.S., Faridi F.R., Efficient Algorithm for Automated Rescue Boats, Proceedings of the 2012 IEEE 16th International Conference on Computer Supported Cooperative Work in Design
- [17] Ren Z., Feng Z., Wang X., An Efficient Ant Colony Optimization Approach to Agent Coalition Formation Problem, Proceedings of the 7th World Congress on Intelligent Control and Automation; June 25-27, 2008, Chongqing, China
- [18] Sujit P.B., Ghose D., Self Assessment-Based Decision Making for Multiagent Cooperative Search, IEEE Transactions on Automation Science and Engineering, Vol. 8, No. 4, October 2011
- [19] Karoń I., Gugała K., Pochmara J., Rybarczyk A., FPGA implementation of the Predator-Prey with adrenalin boost based on a Spiking Neural Network, Elektronika, konstrukcje technologie, zastosowania, vol. 12(2012), 25-28
Typ dokumentu
Bibliografia
Identyfikator YADDA
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