Supporting Mobility and Negotiation in Agent-Based E-Commerce

2011 ◽  
pp. 226-244
Author(s):  
Ryszard Kowalczyk ◽  
Leila Alem
Keyword(s):  
Decision Making ◽  
Coalition Formation ◽  
Intelligent Agents ◽  
Mobile Agents ◽  
Formation Processes ◽  
Trade Off ◽  
Agent Based ◽  
Recent Advances

This chapter presents recent advances in agent-based e-commerce, addressing the issues of mobility and negotiation. It reports on selected research efforts, focusing on developing intelligent agents for automating the e-commerce negotiation and coalition formation processes and mobile agents for supporting deployment of intelligent e-commerce agents and enabling mobile e-commerce applications. Issues such as trade-off between decision-making in negotiation and mobility capabilities of the agents are also discussed in this paper.

scholarly journals Agent based model

2020 ◽  
Vol 55 ◽  
pp. S187-S191 ◽  
Author(s):  
S. Bai ◽  
W. Raskob ◽  
T. Müller
Keyword(s):  
Decision Making ◽  
Emergency Management ◽  
Intelligent Agents ◽  
Decision Making Process ◽  
Agent Based Model ◽  
Radiological Emergency ◽  
Agent Based ◽  
Computational Implementation ◽  
Protection Strategies ◽  
Decision Making Processes

In the CONFIDENCE project, we developed an agent based model (ABM) to simulate the decision making process involving stakeholders of different interests. Our model aims to support decisions on the most suitable protection strategies in different accident phases. The intelligent agents and the models of the negotiation/voting process are described in the paper. Given five scenarios, the numerical results from the computational implementation of the ABM are visualized and analysed in order to better understand the negotiation and voting processes. Our ABM can be expanded in order to support the decision making processes of many different stakeholders of various types of risk management apart from nuclear and radiological emergency management.

scholarly journals Agent based Decision Support System for Travelers

2020 ◽  
pp. 293-298
Author(s):  
Thi Thi Tun ◽  
Prof Thwe
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Information Systems ◽  
Decision Support System ◽  
Decision Support Systems ◽  
Support System ◽  
Intelligent Agents ◽  
Decision Making Process ◽  
Agent Based ◽  
Travel Planning

Nowadays, management of the travelers to support their recreation or holiday planning is increasingly becoming important and popular. Planning a trip needs to assemble a wide variety of information from a large number of sources, such as car schedule and prices, hotel locations, the map of traveled places, etc. Now, this information is available in this system and it can be used to decide a better plan traveler. Decision support systems are the type of information systems expressly developed to support the decision making process and to assist a decision maker. So, this system is implemented as the decision support system for travelling. Moreover, this system describes the use of intelligent agents for extracting and integrating data to improve the ability to plan a travel. These agents can extract data, integrate this data to support travel planning and monitor all aspects of a trip. Therefore, a traveler decision support system by using intelligent agents will develop to support travelers in making their decision on a suitable track when they are faced with a number of alternative track options.

scholarly journals Agent Based Resilient Transportation Infrastructure With Surrogate Adaptive Networks

2020 ◽  
Author(s):  
Andre A. Apostol ◽  
Cameron J. Turner
Keyword(s):  
Decision Making ◽  
Traffic Flow ◽  
Intelligent Agents ◽  
Autonomous Vehicle ◽  
Transportation Infrastructure ◽  
Adaptive Networks ◽  
Agent Based ◽  
Vehicle To Vehicle ◽  
Vehicle To Infrastructure ◽  
Vehicle Technology

Abstract Connected autonomous intelligent agents (AIA) can improve intersection performance and resilience for the transportation infrastructure. An agent is an autonomous decision maker whose decision making is determined internally but may be altered by interactions with the environment or with other agents. Implementing agent-based modeling techniques to advance communication for more appropriate decision making can benefit autonomous vehicle technology. This research examines vehicle to vehicle (V2V), vehicle to infrastructure (V2I), and infrastructure to infrastructure (I2I) communication strategies that use gathered data to ensure these agents make appropriate decisions under operational circumstances. These vehicles and signals are modeled to adapt to the common traffic flow of the intersection to ultimately find an traffic flow that will minimizes average vehicle transit time to improve intersection efficiency. By considering each light and vehicle as an agent and providing for communication between agents, additional decision-making data can be transmitted. Improving agent based I2I communication and decision making will provide performance benefits to traffic flow capacities.

scholarly journals Agent-Based Dispatching Enables Autonomous Groupage Traffic

2013 ◽  
Vol 3 (1) ◽  
pp. 27-40 ◽  
Author(s):  
Max Gath ◽  
Stefan Edelkamp ◽  
Otthein Herzog
Keyword(s):  
Decision Making ◽  
Intelligent Agents ◽  
Time Windows ◽  
Reactive System ◽  
Adaptive Planning ◽  
Routing Problem ◽  
Agent Based ◽  
Practical Applications ◽  
Planning And Control ◽  
The Individual

Abstract The complexity and dynamics in groupage traffic require flexible, efficient, and adaptive planning and control processes. The general problem of allocating orders to vehicles can be mapped into the Vehicle Routing Problem (VRP). However, in practical applications additional requirements complicate the dispatching processes and require a proactive and reactive system behavior. To enable automated dispatching processes, this article presents a multiagent system where the decision making is shifted to autonomous, interacting, intelligent agents. Beside the communication protocols and the agent architecture, the focus is on the individual decision making of the agents which meets the specific requirements in groupage traffic. To evaluate the approach we apply multiagent-based simulation and model several scenarios of real world infrastructures with orders provided by our industrial partner. Moreover, a case study is conducted which covers the autonomous groupage traffic in the current processes of our industrial parter. The results reveal that agent-based dispatching meets the sophisticated requirements of groupage traffic. Furthermore, the decision making supports the combination of pickup and delivery tours efficiently while satisfying logistic request priorities, time windows, and capacity constraints.

Sign in / Sign up

Export Citation Format

Share Document