A negotiation strategy for the Temporal Resource Reallocation Problem in multi-agent systems

2008 ◽  
Vol 3 (3) ◽  
pp. 194
Author(s):  
Panos Alexopoulos ◽  
Manolis Wallace
2013 ◽  
Vol 651 ◽  
pp. 943-948
Author(s):  
Zhi Ling Hong ◽  
Mei Hong Wu

In multi-agent systems, a number of autonomous pieces of software (the agents) interact in order to execute complex tasks. This paper proposes a logic framework portrays agent’s communication protocols in the multi-agent systems and a dynamic negotiation model based on epistemic default logic was introduced in this framework. In this paper, we use the constrained default rules to investigate the extension of dynamic epistemic logic, and constrained epistemic extension construct an efficient negotiation strategy via constrained epistemic default reasoning, which guarantees the important natures of extension existence and semi-monotonicity. We also specify characteristic of the dynamic updating when agent learn new knowledge in the logical framework. The method for the information sharing signify the usefulness of logical tools carried out in the dynamic process of information acquisition, and the distributed intelligent information processing show the effectiveness of reasoning default logic in the dynamic epistemic logic theory.


Author(s):  
Jana Dospisil

Agents are viewed as the next significant software abstraction, and it is expected they will become as ubiquitous as graphical user interfaces are today. Multi-agent systems have a key capability to reallocate tasks among their members, and this may result in significant savings and improvements in many domains, such as resource allocation, scheduling, e-commerce, etc. In the near future, agents will roam the Internet, selling and buying information and services. These agents will evolve from their present-day form—simple carriers of transactions—to efficient decision makers. It is envisaged that the decision-making processes and interactions between agents will be very fast (Kephart, 1998). The importance of automated negotiation systems is increasing with the emergence of new technologies supporting faster reasoning engines and mobile code. A central part of agent systems is a sophisticated reasoning engine that enables the agents to reallocate their tasks, optimize outcomes, and negotiate with other agents. The negotiation strategy used by the reasoning engine also requires high-level interagent communication protocols and suitable collaboration strategies. Both of these subsystems—a reasoning engine and a collaboration strategy—typically result in complicated agent designs and implementations that are difficult to maintain.


Sign in / Sign up

Export Citation Format

Share Document