scholarly journals Application of an Encoding Revision Algorithm in Overlapping Coalition Formation

2021 ◽  
Vol 15 (4) ◽  
pp. 0-0
Keyword(s):  
Coalition Formation ◽  
Research Field ◽  
Limited Resources ◽  
Multi Agent Systems ◽  
Solution Quality ◽  
Resource Conflicts ◽  
Experimental Platform ◽  
Multiple Tasks ◽  
Multi Agent ◽  
Active Research

Overlapping coalition formation is a very active research field in multi-agent systems (MAS). In overlapping coalition, each agent can participate in different coalitions corresponding to multiple tasks at the same time. As each agent has limited resources, resource conflicts will occur. In order to resolve resource conflicts, we develop an improved encoding revision algorithm in this paper which can revise an invalid two-dimensional binary encoding into a valid one by checking the encoding for each row. To verify the effectiveness of the algorithm, differential evolution was used as the experimental platform and compared with Zhang et al. The experimental results show that the algorithm in this paper is superior to Zhang et al. in both solution quality and encoding revision time.

scholarly journals Application of an Encoding Revision Algorithm in Overlapping Coalition Formation

2021 ◽  
Vol 15 (4) ◽  
pp. 1-20
Author(s):  
Haixia Gui ◽  
Banglei Zhao ◽  
Huizong Li ◽  
Wanliu Che
Keyword(s):  
Coalition Formation ◽  
Research Field ◽  
Limited Resources ◽  
Multi Agent Systems ◽  
Solution Quality ◽  
Resource Conflicts ◽  
Experimental Platform ◽  
Multiple Tasks ◽  
Multi Agent ◽  
Active Research

Overlapping coalition formation is a very active research field in multi-agent systems (MAS). In overlapping coalition, each agent can participate in different coalitions corresponding to multiple tasks at the same time. As each agent has limited resources, resource conflicts will occur. In order to resolve resource conflicts, we develop an improved encoding revision algorithm in this paper which can revise an invalid two-dimensional binary encoding into a valid one by checking the encoding for each row. To verify the effectiveness of the algorithm, differential evolution was used as the experimental platform and compared with Zhang et al. The experimental results show that the algorithm in this paper is superior to Zhang et al. in both solution quality and encoding revision time.

scholarly journals A multi-responsibility–oriented coalition formation framework for dynamic task allocation in mobile–distributed multi-agent systems

2018 ◽  
Vol 15 (6) ◽  
pp. 172988141881303 ◽  
Author(s):  
Bing Xie ◽  
Xueqiang Gu ◽  
Jing Chen ◽  
LinCheng Shen
Keyword(s):  
Coalition Formation ◽  
Task Allocation ◽  
Game Model ◽  
Multi Agent Systems ◽  
Coalition Game ◽  
Task Execution ◽  
Agent Systems ◽  
Dynamic Task ◽  
Dynamic Task Allocation ◽  
Multi Agent

In this article, we study a problem of dynamic task allocation with multiple agent responsibilities in distributed multi-agent systems. Agents in the research have two responsibilities, communication and task execution. Movements in agent task execution bring changes to the system network structure, which will affect the communication. Thus, agents need to be autonomous on communication network reconstruction for good performance on task execution. First, we analyze the relationships between the two responsibilities of agents. Then, we design a multi-responsibility–oriented coalition formation framework for dynamic task allocation with two parts, namely, task execution and self-adaptation communication. For the former part, we integrate our formerly proposed algorithm in the framework for task execution coalition formation. For the latter part, we develop a constrained Bayesian overlapping coalition game model to formulate the communication network. A task-allocation efficiency–oriented communication coalition utility function is defined to optimize a coalition structure for the constrained Bayesian overlapping coalition game model. Considering the geographical location dependence between the two responsibilities, we define constrained agent strategies to map agent strategies to potential location choices. Based on the abovementioned design, we propose a distributed location pruning self-adaptive algorithm for the constrained Bayesian overlapping coalition formation. Finally, we test the performance of our framework, multi-responsibility–oriented coalition formation framework, with simulation experiments. Experimental results demonstrate that the multi-responsibility oriented coalition formation framework performs better than the other two distributed algorithms on task completion rate (by over 9.4% and over 65% on average, respectively).

scholarly journals Representation and Reasoning about Strategic Abilities with ω-Regular Properties

Mathematics ◽  
2021 ◽  
Vol 9 (23) ◽  
pp. 3052
Author(s):  
Liping Xiong ◽  
Sumei Guo
Keyword(s):  
Temporal Logic ◽  
Linear Time ◽  
Dynamic Logic ◽  
Research Area ◽  
Regular Expressions ◽  
Multi Agent Systems ◽  
Practical Applications ◽  
Multi Agent ◽  
Strategy Logic ◽  
Active Research

Specification and verification of coalitional strategic abilities have been an active research area in multi-agent systems, artificial intelligence, and game theory. Recently, many strategic logics, e.g., Strategy Logic (SL) and alternating-time temporal logic (ATL*), have been proposed based on classical temporal logics, e.g., linear-time temporal logic (LTL) and computational tree logic (CTL*), respectively. However, these logics cannot express general ω-regular properties, the need for which are considered compelling from practical applications, especially in industry. To remedy this problem, in this paper, based on linear dynamic logic (LDL), proposed by Moshe Y. Vardi, we propose LDL-based Strategy Logic (LDL-SL). Interpreted on concurrent game structures, LDL-SL extends SL, which contains existential/universal quantification operators about regular expressions. Here we adopt a branching-time version. This logic can express general ω-regular properties and describe more programmed constraints about individual/group strategies. Then we study three types of fragments (i.e., one-goal, ATL-like, star-free) of LDL-SL. Furthermore, we show that prevalent strategic logics based on LTL/CTL*, such as SL/ATL*, are exactly equivalent with those corresponding star-free strategic logics, where only star-free regular expressions are considered. Moreover, results show that reasoning complexity about the model-checking problems for these new logics, including one-goal and ATL-like fragments, is not harder than those of corresponding SL or ATL*.

scholarly journals Contextual and Possibilistic Reasoning for Coalition Formation

AI ◽  
2020 ◽  
Vol 1 (3) ◽  
pp. 389-417
Author(s):  
Antonis Bikakis ◽  
Patrice Caire
Keyword(s):  
Coalition Formation ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Contextual Reasoning ◽  
Multi Agent

In multi-agent systems, agents often need to cooperate and form coalitions to fulfil their goals, for example by carrying out certain actions together or by sharing their resources. In such situations, some questions that may arise are: Which agent(s) to cooperate with? What are the potential coalitions in which agents can achieve their goals? As the number of possibilities is potentially quite large, how to automate the process? And then, how to select the most appropriate coalition, taking into account the uncertainty in the agents’ abilities to carry out certain tasks? In this article, we address the question of how to identify and evaluate the potential agent coalitions, while taking into consideration the uncertainty around the agents’ actions. Our methodology is the following: We model multi-agent systems as Multi-Context Systems, by representing agents as contexts and the dependencies among agents as bridge rules. Using methods and tools for contextual reasoning, we compute all possible coalitions with which the agents can fulfil their goals. Finally, we evaluate the coalitions using appropriate metrics, each corresponding to a different requirement. To demonstrate our approach, we use an example from robotics.

Trust-based coalition formation in multi-agent systems

2012 ◽  
Vol 11 (1) ◽  
pp. 19-32 ◽  
Author(s):  
Dariusz G Mikulski ◽  
Frank L Lewis ◽  
Edward Y Gu ◽  
Greg R Hudas
Keyword(s):  
Coalition Formation ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Multi Agent

Negotiation in Agent Based Manufacturing Scheduling Using Auction Models

2005 ◽  
Author(s):  
Chun Wang ◽  
Weiming Shen ◽  
Hamada Ghenniwa
Keyword(s):  
Theoretical Models ◽  
Shop Floor ◽  
Multi Agent Systems ◽  
Solution Quality ◽  
Manufacturing Scheduling ◽  
Agent Based ◽  
Auction Models ◽  
Auction Mechanisms ◽  
Multi Agent

This paper investigates issues in the application of auctions as negotiation mechanisms to agent based manufacturing scheduling. We model the negotiation environments that agents encounter as inter-enterprise environment and intra-enterprise environment. A formulation of intra-enterprise scheduling economy is presented. We proved that at price equilibrium, the solution computed by the agents in the economy is a Pareto optimal. AS our first attempt, we formally formulate automated auction configuration as an optimization problem. By solving the problem adaptive negotiation in multi-agent systems can be achieved. In addition to the theoretical models, we discussed various types of auction mechanisms and their applications to agent based manufacturing scheduling. Heuristics and procedures are proposed for solving the automated auction configuration problem. To validate the analysis and proposed approaches, as a case study, we apply the automated auction configuration heuristics and the procedure to an agent based shop floor scheduling environment. Experimental results show that the auction protocol selected by the proposed heuristics provides correct system functionalities. In addition, we compared the selected mechanism with other candidate mechanisms. We found that the selected one performs better in terms of reducing communication cost and improving solution quality.

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