Highest Degree Likelihood Search Algorithm Using a State Transition Matrix for Complex Networks

Feng, Minyu; Qu, Hong; Zhang, Yi

doi:10.1109/tcsi.2014.2333677

Cited by 14 publications

(8 citation statements)

References 23 publications

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“…Therefore, some researches adopt the definition of Partially Observable Stochastic Game (POSG), and a cooperative case of POSG, namely Dec-POMDP [ 20 ]. Although some efforts have been made in building heuristic algorithms to solve this intrinsic NEXP-complete problem [ 21 ], it is still less feasible obtaining optimal results in a limited time with the partial observation over channels. In addition, in a non-cooperative case, this Dec-POMDP will no longer be suitable.…”

Section: State Of the Artmentioning

confidence: 99%

“…The goal of this problem’s model is to come up with a joint policy Π* = , which can maximize the expected reward of all the agents over a finite horizon. The belief space is a sufficient statistic [ 21 ], and can be independent of the decision time. We remark that r i can only infer what action its neighbors may take, but the inference or conflict is inevitable.…”

Section: A Resource-aware Approach For Multi-agent Multi-channel Accementioning

confidence: 99%

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Decentralized Opportunistic Spectrum Resources Access Model and Algorithm toward Cooperative Ad-Hoc Networks

Liu

Mohammed

2016

PLoS ONE

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Limited communication resources have gradually become a critical factor toward efficiency of decentralized large scale multi-agent coordination when both system scales up and tasks become more complex. In current researches, due to the agent’s limited communication and observational capability, an agent in a decentralized setting can only choose a part of channels to access, but cannot perceive or share global information. Each agent’s cooperative decision is based on the partial observation of the system state, and as such, uncertainty in the communication network is unavoidable. In this situation, it is a major challenge working out cooperative decision-making under uncertainty with only a partial observation of the environment. In this paper, we propose a decentralized approach that allows agents cooperatively search and independently choose channels. The key to our design is to build an up-to-date observation for each agent’s view so that a local decision model is achievable in a large scale team coordination. We simplify the Dec-POMDP model problem, and each agent can jointly work out its communication policy in order to improve its local decision utilities for the choice of communication resources. Finally, we discuss an implicate resource competition game, and show that, there exists an approximate resources access tradeoff balance between agents. Based on this discovery, the tradeoff between real-time decision-making and the efficiency of cooperation using these channels can be well improved.

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Section: State Of the Artmentioning

confidence: 99%

Section: A Resource-aware Approach For Multi-agent Multi-channel Accementioning

confidence: 99%

Decentralized Opportunistic Spectrum Resources Access Model and Algorithm toward Cooperative Ad-Hoc Networks

Liu

Mohammed

2016

PLoS ONE

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“…Therefore, some researches adapt the definition of Partially Observable Stochastic Game (POSG): a cooperative case of POSG, namely Decentralized Partially Observable Markov Decision Process (Dec-POMDP) [13]. Although extra efforts have been made in building heuristic algorithms to solve this problem, but it is still be NEXP-complete [14].…”

Section: State Of the Artmentioning

confidence: 99%

“…The goal of this problem's model is to come up with a joint policy Π * =× 1≤i≤N π t i , which can maximize the expected reward of all the robots over a finite horizon. The belief space is a sufficient statistic [14] and can be independent of the decision time. We remark that r i can only infer what action its neighbors may take, but the inference or conflict is inevitable.…”

Section: B Dynamic Local Searchmentioning

confidence: 99%

“…But from a practical view point, each robot can be aware of its neighbor, and therefore, with the neighbor's policy sharing, robot r i can get a proximity full local observation. Consequently, we refer to the design in [14], and the multi-robot finite horizon Dec-POMDP model can decompose into serval single-robot POMDP decision problems.…”

Section: A Decision Theoretical Approach For Multi-channel Access mentioning

confidence: 99%

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Decentralized Channel Access Mechanism Design for Multi-robot Coordination

Liu

2015

2015 IEEE International Conference on Systems, Man, and Cybernetics

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With the expansion of decentralized multi-robot system's applications, limited communication resources has become a critical factor toward the efficiency of multi-robot coordination when both system sizes scale up and their tasks become more complex. In current researches, it is only possible for every robot in a decentralized setting either to choose a part of communication channels to communicate or interact with the other robots. However, due to the constraint on robots' limited communication capability as well as their local observations of the whole network, each robot's cooperative communication channel choice, based on the partial observation of the states of the system, and communication network is under uncertainty. It is also a major challenge to work out multi-robots' cooperative decision by uncertainty reasoning with only a partial observation to the environment. In this paper, we propose a decentralized approach that allows robots to cooperatively search channels and independently choose channels. The key of this approach is to build an up-to-date observation for each robot's view so that a local decision model is achievable. Based on this model, we simplify the Dec-POMDP problem model and each robot can jointly work out its communication policy in order to improve its local decision utilities for the choice of the communication channel using its current observation of the limited system's states as well as its neighbors' choices. In this way, an approximate balance between timeliness of decisionmaking and cooperatively enhancing the efficiency of using these channels can be reached.

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