Automatized Decision Making for Autonomous Agents

Author(s):  
Love Ekenberg ◽  
Mats Danielson

Utility theory and the principle of maximising the expected utility have, within the multi-agent community, had a great influence on multi-agent based decision. Even though this principle is often useful when evaluating a decision situation it is virtually impossible, except in very artificial situations, to use the more basic decision rules with its unrealistically strong requirements for the input data, and other candidate methods must be considered instead. This article provides an overview and brings attention to some of the possibilities to utilize more elaborated decision methods, while still keeping the computational issues at a tractable level.

Author(s):  
Takeshi Takenaka ◽  
Kousuke Fujita ◽  
Nariaki Nishino ◽  
Tsukasa Ishigaki ◽  
Yoichi Motomura

Science and technology are expected to support actual service provision and to create new services to promote service industries’ productivity. However, those problems might not be solved solely in a certain research area. This paper describes that it is necessary to establish transdisciplinary approaches to service design in consideration of consumers’ values and decision making. Recent research trends of services are overviewed. Then a research framework is proposed to integrate computer sciences, human sciences, and economic sciences. Three study examples of services are then presented. The first study is a multi-agent simulation of a cellular telephone market based on results of a psychological survey. The second presents a cognitive model constructed through integration of questionnaire data of a retail business and Bayesian network modeling. The third presents a pricing mechanism design for service facilities––movie theaters––using an economic experiment and agent-based simulation.


Author(s):  
El Habib Nfaoui ◽  
Omar El Beqqali ◽  
Yacine Ouzrout ◽  
Abdelaziz Bouras

Decisions at different levels of the supply chain can no longer be considered independently, since they may influence profitability throughout the supply chain. This paper focuses on the interest of multi-agent paradigm for the collaborative coordination in global distribution supply chain. Multi-agent computational environments are suitable for a broad class of coordination and negotiation issues involving multiple autonomous or semiautonomous problem solving contexts. An agent-based distributed architecture is proposed for better management of rush unexpected orders. This paper proposes a first architecture validated by a real and industrial case.


2013 ◽  
Vol 710 ◽  
pp. 781-785 ◽  
Author(s):  
Li Zhang ◽  
Zhi Qi ◽  
Hao Cui ◽  
Sen Hua Wang ◽  
Ya Hui Ning ◽  
...  

Aiming at the requirements of urgency and dynamics in emergency logistics, this paper presents a multi-agent system (MAS) concept model for emergency logistics collaborative decision making. The suggested model includes three kinds of agents, i.e., role agent, function agent and assistant agent. Role agent excutes emergency logistics activities, function agent achieves the task requirements in every work phase and assistant agent helps organizing and visiting data. Two levels agent views serve as the basic skeleton of the MAS. Top level is the global decision-making view, which describes the task distribution process with multiple agents. Local level is the execution planning view, which simulates task executing process of the performer. Finally, an extended BDI agent structure model is proposed to help the implementation at application level.


Author(s):  
Takeshi Takenaka ◽  
Kousuke Fujita ◽  
Nariaki Nishino ◽  
Tsukasa Ishigaki ◽  
Yoichi Motomura

Science and technology are expected to support actual service provision and to create new services to promote service industries’ productivity. However, those problems might not be solved solely in a certain research area. This paper describes that it is necessary to establish transdisciplinary approaches to service design in consideration of consumers’ values and decision making. Recent research trends of services are overviewed. Then a research framework is proposed to integrate computer sciences, human sciences, and economic sciences. Three study examples of services are then presented. The first study is a multi-agent simulation of a cellular telephone market based on results of a psychological survey. The second presents a cognitive model constructed through integration of questionnaire data of a retail business and Bayesian network modeling. The third presents a pricing mechanism design for service facilities––movie theaters––using an economic experiment and agent-based simulation.


Author(s):  
Michael Laver ◽  
Ernest Sergenti

This chapter begins with a brief discussion of the need for a new approach to modeling party competition. It then makes a case for the use of agent-based modeling to study multiparty competition in an evolving dynamic party system, given the analytical intractability of the decision-making environment, and the resulting need for real politicians to rely on informal decision rules. Agent-based models (ABMs) are “bottom-up” models that typically assume settings with a fairly large number of autonomous decision-making agents. Each agent uses some well-specified decision rule to choose actions, and there may be considerable diversity in the decision rules used by different agents. Given the analytical intractability of the decision-making environment, the decision rules that are specified and investigated in ABMs are typically based on adaptive learning rather than forward-looking strategic analysis, and agents are assumed to have bounded rather than perfect rationality. An overview of the subsequent chapters is also presented.


2014 ◽  
Vol 6 (4) ◽  
pp. 72-91
Author(s):  
Timothy W. C. Johnson ◽  
John R. Rankin

Large-scale Agent-Based Modelling and Simulation (ABMS) is a field of research that is becoming increasingly popular as researchers work to construct simulations at a higher level of complexity and realism than previously done. These systems can not only be difficult and time consuming to implement, but can also be constrained in their scope due to issues arising from a shortage of available processing power. This work simultaneously presents solutions to these two problems by demonstrating a model for ABMS that allows a developer to design their own simulation, which is then automatically converted into code capable of running on a mainstream Graphical Processing Unit (GPU). By harnessing the extra processing power afforded by the GPU this paper creates simulations that are capable of running in real-time with more autonomous agents than allowed by systems using traditional x86 processors.


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