Modeling communication of collaborative multiagent system under epistemic planning

Efficient MapReduce secure data using Multiagent System

International Journal of Computer Sciences and Engineering ◽

10.26438/ijcse/v6i5.144149 ◽

2018 ◽

Vol 6 (5) ◽

pp. 144-149

Author(s):

H. Kousar ◽

◽

B.R.P. Babu

Keyword(s):

Multiagent System ◽

Secure Data

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A fully distributed method for distributed multiagent system in a microgrid

Energy Reports ◽

10.1016/j.egyr.2021.03.035 ◽

2021 ◽

Vol 7 ◽

pp. 2294-2301

Author(s):

Diyako Ghaderyan ◽

Fernando Lobo Pereira ◽

A. Pedro Aguiar

Keyword(s):

Multiagent System ◽

Distributed Method

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A Generalized Dynamic Potential Energy Model for Multiagent Path Planning

Journal of Advanced Transportation ◽

10.1155/2020/1360491 ◽

2020 ◽

Vol 2020 ◽

pp. 1-14

Author(s):

Liu He ◽

Haoning Xi ◽

Tangyi Guo ◽

Kun Tang

Keyword(s):

Path Planning ◽

Potential Energy ◽

Multiagent System ◽

Small Time ◽

Energy Model ◽

Dijkstra Algorithm ◽

Energy Field ◽

Space Potential ◽

Dynamic Potential ◽

Planning Decision

Path planning for the multiagent, which is generally based on the artificial potential energy field, reflects the decision-making process of pedestrian walking and has great importance on the field multiagent system. In this paper, after setting the spatial-temporal simulation environment with large cells and small time segments based on the disaggregation decision theory of the multiagent, we establish a generalized dynamic potential energy model (DPEM) for the multiagent through four steps: (1) construct the space energy field with the improved Dijkstra algorithm, and obtain the fitting functions to reflect the relationship between speed decline rate and space occupancy of the agent through empirical cross experiments. (2) Construct the delay potential energy field based on the judgement and psychological changes of the multiagent in the situations where the other pedestrians have occupied the bottleneck cell. (3) Construct the waiting potential energy field based on the characteristics of the multiagent, such as dissipation and enhancement. (4) Obtain the generalized dynamic potential energy field by superposing the space potential energy field, delay potential energy field, and waiting potential energy field all together. Moreover, a case study is conducted to verify the feasibility and effectiveness of the dynamic potential energy model. The results also indicate that each agent’s path planning decision such as forward, waiting, and detour in the multiagent system is related to their individual characters and environmental factors. Overall, this study could help improve the efficiency of pedestrian traffic, optimize the walking space, and improve the performance of pedestrians in the multiagent system.

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