Multi-agent system

About: Multi-agent system is a research topic. Over the lifetime, 27978 publications have been published within this topic receiving 465191 citations. The topic is also known as: multi-agent systems & multiagent system.

Holonic Multiagent Systems: A Foundation for the Organisation of Multiagent Systems

Abstract: With the growing usage of the world-wide ICT networks, agent technologies and multiagent systems are attracting more and more attention, as they perform well in environments that are not necessarily well-structured and benevolent. Looking at the problem solving capacity of multiagent systems, emergent system behaviour is one of the most interesting phenomena, however, there is more to multiagent systems design than the interaction between a number of agents: For an effective system behaviour we need structure and organisation. But the organisation of a multiagent systems is difficult to specify at design time in the face of a changing environment.

Multi-Agent-Systems Based on Coloured Petri Nets

Abstract: Based on Y. Shoham's paradigm, called Agent-Oriented Programming (AOP), multi-agent-systems are presented as a specialization of distributed, Object-Oriented systems. Equipped with knowledge, general concurrent inference mechanisms dealing with this knowledge, and a declarative agent program, these multi-agent-systems are intended to be a foundation of a new approach uniting advantages of many contributing areas: The precise semantics of Petri nets, the abstraction and encapsulation proposed in Object-Oriented approaches, and the power of logic programming, making it easy to adopt well-known AI-methods. As an example, an urban traffic information system will be designed which solves path searching problems in a distributed graph.

A multiagent model of the UK market in electricity generation

Abstract: The deregulation of electricity markets has continued apace around the globe. The best structure for deregulated markets is a subject of much debate, and the consequences of poor structural choices can be dramatic. Understanding the effect of structure on behavior is essential, but the traditional economics approaches of field studies and experimental studies are particularly hard to conduct in relation to electricity markets. This paper describes an agent based computational economics approach for studying the effect of alternative structures and mechanisms on behavior in electricity markets. Autonomous adaptive agents, using hierarchical learning classifier systems, learn through competition in a simulated model of the UK market in electricity generation. The complex agent structure was developed through a sequence of experimentation to test whether it was capable of meeting the following requirements: first, that the agents are able to learn optimal strategies when competing against nonadaptive agents; second, that the agents are able to learn strategies observable in the real world when competing against other adaptive agents; and third, that cooperation without explicit communication can evolve in certain market situations. The potential benefit of an evolutionary economics approach to market modeling is demonstrated by examining the effects of alternative payment mechanisms on the behavior of agents.

A Multi-Agent System for Building Control

Abstract: Energy efficiency and occupants' comfort are two important factors for evaluating the performance of a modern work environment. While energy efficiency, pivotal to energy savings, has been improving steadily over the past decades, a great effort has been made to address occupants' comfort, pivotal to work productivity, too. Not surprisingly, many researchers have endeavored to combine the expertise from the two areas to create an intelligent work environment, where energy efficiency is achieved without compromising occupants' comfort. Previous studies provide insightful discussions and exciting experiments. Most of them, however, stopped short of commercialization and adoption in daily life due to the limitations of hardware and software technologies at the time. With the advance of agent technology, wireless sensor network and open standards in building automation/management systems, it is now feasible to build such an intelligent system for energy efficient and occupants satisfied building control, as envisaged and explored by those pioneers. This paper introduces some ongoing research on developing a multi-agent system that combines an EDA agent model, personalized space, policy management, building performance quotient, wireless sensor network, and building automation/management system to provide an intelligent work environment.

A Market Approach to Multirobot Coordination

Abstract: The problem of efficient multirobot coordination has risen to the forefront of robotics research in recent years. Interest in this problem is motivated by the wide range of application domains demanding multirobot solutions. In general, multirobot coordination strategies assume either a centralized approach, where a single robot/agent plans for the group, or a distributed approach, where each robot is responsible for its own planning. Inherent to many centralized approaches are difficulties such as intractable solutions for large groups, sluggish response to changes in the local environment, heavy communication requirements, and brittle systems with single points of failure. The key advantage of centralized approaches is that they can produce globally optimal plans. While most distributed approaches can overcome the obstacles inherent to centralized approaches, they can only produce suboptimal plans. This work explores the development of a market-based architecture that will be inherently distributed, but will also opportunistically form centralized sub-groups to improve efficiency, and thus approach optimality. Robots will be self-interested agents, with the primary goal of maximizing individual profits. The revenue/cost models and rules of engagement will be designed so that maximizing individual profit has the benevolent effect of moving the team toward the globally optimal solution. This architecture will inherit the flexibility of market-based approaches in allowing cooperation and competition to emerge opportunistically. The outlined approach will address the multirobot control problem for autonomous robotic colonies carrying out complex tasks in dynamic environments where it is highly desirable to optimize to whatever extent possible. Future work will develop the core components of a market-based multirobot control-architecture, investigate the use of a negotiation protocol for task distribution, design and implement resource and role management schemes, and apply optimization techniques to improve system performance. The automated robot colonies domain is targeted for implementation and evaluation of the architecture. Portability of the architecture to other application domains will also be illustrated.