Coalition formation algorithm based on organization and Markov decision process for multi-player pursuit evasion

2015 ◽  
Vol 11 (1) ◽  
pp. 1-13 ◽  
Author(s):  
Mohamed Souidi ◽  
Songhao Piao ◽  
Guo Li ◽  
Lin Chang
Keyword(s):  
Markov Decision Process ◽  
Coalition Formation ◽  
Decision Process ◽  
Pursuit Evasion ◽  
Markov Decision

scholarly journals A New Decentralized Approach of Multiagent Cooperative Pursuit Based on the Iterated Elimination of Dominated Strategies Model

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Mohammed El Habib Souidi ◽  
Songhao Piao
Keyword(s):  
Game Theory ◽  
Coalition Formation ◽  
Decision Process ◽  
Pursuit Evasion ◽  
Dominated Strategies ◽  
Markov Decision ◽  
Simulation Results ◽  
The Given ◽  
Dynamic Formation ◽  
Motion Strategy

Game Theory is a promising approach to acquire coalition formations in multiagent systems. This paper is focused on the importance of the distributed computation and the dynamic formation and reformation of pursuit groups in pursuit-evasion problems. In order to address this task, we propose a decentralized coalition formation algorithm based on the Iterated Elimination of Dominated Strategies (IEDS). This Game Theory process is common to solve problems requiring the withdrawal of dominated strategies iteratively. Furthermore, we have used the Markov Decision Process (MDP) principles to control the motion strategy of the agents in the environment. The simulation results demonstrate the feasibility and the validity of the given approach in comparison with different decentralized methods.

A Continuous-time Markov Decision Process Based Method on Pursuit-Evasion Problem

2014 ◽  
Vol 47 (3) ◽  
pp. 620-625 ◽  
Author(s):  
Jia Shengde ◽  
Wang Xiangke ◽  
Ji Xiaoting ◽  
Zhu Huayong
Keyword(s):  
Markov Decision Process ◽  
Continuous Time ◽  
Decision Process ◽  
Pursuit Evasion ◽  
Markov Decision ◽  
Evasion Problem

scholarly journals Development of a Shipment Policy for Collection Centers

Mathematics ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 1385
Author(s):  
Irais Mora-Ochomogo ◽  
Marco Serrato ◽  
Jaime Mora-Vargas ◽  
Raha Akhavan-Tabatabaei
Keyword(s):  
Climate Change ◽  
Natural Disasters ◽  
Markov Decision Process ◽  
Decision Process ◽  
Necessary Conditions ◽  
Decision Makers ◽  
Humanitarian Organizations ◽  
The World ◽  
Markov Decision ◽  
Unsatisfied Demand

Natural disasters represent a latent threat for every country in the world. Due to climate change and other factors, statistics show that they continue to be on the rise. This situation presents a challenge for the communities and the humanitarian organizations to be better prepared and react faster to natural disasters. In some countries, in-kind donations represent a high percentage of the supply for the operations, which presents additional challenges. This research proposes a Markov Decision Process (MDP) model to resemble operations in collection centers, where in-kind donations are received, sorted, packed, and sent to the affected areas. The decision addressed is when to send a shipment considering the uncertainty of the donations’ supply and the demand, as well as the logistics costs and the penalty of unsatisfied demand. As a result of the MDP a Monotone Optimal Non-Decreasing Policy (MONDP) is proposed, which provides valuable insights for decision-makers within this field. Moreover, the necessary conditions to prove the existence of such MONDP are presented.

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