Goran Zaharija
; Faculty of Science, University of Split, Croatia
Saša Mladenović
; Faculty of Science, University of Split, Croatia
Lada Maleš
; Faculty of Humanities and Social Sciences, University of Split, Croatia
APA 6th Edition Zaharija, G., Mladenović, S. i Maleš, L. (2017). Unibot, a Universal Agent Architecture for Robots. Journal of computing and information technology, 25 (1), 31-45. https://doi.org/10.20532/cit.2017.1003573
MLA 8th Edition Zaharija, Goran, et al. "Unibot, a Universal Agent Architecture for Robots." Journal of computing and information technology, vol. 25, br. 1, 2017, str. 31-45. https://doi.org/10.20532/cit.2017.1003573. Citirano 04.03.2021.
Chicago 17th Edition Zaharija, Goran, Saša Mladenović i Lada Maleš. "Unibot, a Universal Agent Architecture for Robots." Journal of computing and information technology 25, br. 1 (2017): 31-45. https://doi.org/10.20532/cit.2017.1003573
Harvard Zaharija, G., Mladenović, S., i Maleš, L. (2017). 'Unibot, a Universal Agent Architecture for Robots', Journal of computing and information technology, 25(1), str. 31-45. https://doi.org/10.20532/cit.2017.1003573
Vancouver Zaharija G, Mladenović S, Maleš L. Unibot, a Universal Agent Architecture for Robots. Journal of computing and information technology [Internet]. 2017 [pristupljeno 04.03.2021.];25(1):31-45. https://doi.org/10.20532/cit.2017.1003573
IEEE G. Zaharija, S. Mladenović i L. Maleš, "Unibot, a Universal Agent Architecture for Robots", Journal of computing and information technology, vol.25, br. 1, str. 31-45, 2017. [Online]. https://doi.org/10.20532/cit.2017.1003573
Sažetak Today there are numerous robots in different applications domains despite the fact that they still have limitations in perception, actuation and decision process. Consequently, robots usually have limited autonomy, they are domain specific or have difficulty to adapt on new environments. Learning is the property that makes an agent intelligent and the crucial property that a robot should have to proliferate into the human society. Embedding the learning ability into the robot may simplify the development of the robot control mechanism. The motivation for this research is to develop the agent architecture of the universal robot – Unibot. In our approach the agent is the robot i.e. Unibot that acts in the physical world and is capable of learning. The Unibot conducts several simultaneous simulations of a problem of interest like path-finding. The novelty in our approach is the Multi-Agent Decision Support System which is developed and integrated into the Unibot agent architecture in order to execute simultaneous simulations. Furthermore, the Unibot calculates and evaluates between multiple solutions, decides which action should be performed and performs the action. The prototype of the Unibot agent architecture is described and evaluated in the experiment supported by the Lego Mindstorms robot and the NetLogo.