Anytime Coalition Structure Generation with Worst Case Guarantees

Coalition formation is a key topic in multiagent systems. One would prefer a coalition structure that maximizes the sum of the values of the coalitions, but often the number of coalition structures is too large to allow exhaustive search for the optimal one. But then, can the coalition structure found via a partial search be guaranteed to be within a bound from optimum? We show that none of the previous coalition structure generation algorithms can establish any bound because they search fewer nodes than a threshold that we show necessary for establishing a bound. We present an algorithm that establishes a tight bound within this minimal amount of search, and show that any other algorithm would have to search strictly more. The fraction of nodes needed to be searched approaches zero as the number of agents grows. If additional time remains, our anytime algorithm searches further, and establishes a progressively lower tight bound. Surprisingly, just searching one more node drops the bound in half. As desired, our algorithm lowers the bound rapidly early on, and exhibits diminishing returns to computation. It also drastically outperforms its obvious contenders. Finally, we show how to distribute the desired search across self-interested manipulative agents

09201 Abstracts Collection -- Self-Healing and Self-Adaptive Systems

From May 10th 2009 to May 15th 2009 the Dagstuhl Seminar 09201 ``Self-Healing and Self-Adaptive Systems\u27\u27 was held in Schloss Dagstuhl~--~Leibniz Center for Informatics. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar are put together in this paper. Links to extended abstracts or full papers are provided, if available. A description of the seminar topics, goals and results in general can be found in a separate document ``Executive Summary\u27\u27

Spawning Information Agents on the Web

. Network bandwidth limitations must be considered by information agents when retrieving information from remote sources. There are cases where it should be more efficient (considering network constraints) that an agent will perform its activity on the remote server. This can be performed by spawning an agent on that server. Agent spawning is an appropriate means for resolving agent overload problems as well. Agents in a multi-agent system may face situations where tasks overload their computational capacities or do not fit their capabilities. Usually, this problem is solved by passing tasks to other agents or agent migration to remote hosts. Agent spawning is a more comprehensive approach to balancing local agent overloads. According to our paradigm, agents may spawn, pass tasks to others, die or merge. We discuss the mechanisms required for deciding upon and performing agent spawning. The requirements for implementing a spawning mechanism and the advantages of using it are addressed...

Architectural Properties of Multi-Agent Systems

One aspect of multi-agent systems (MAS) that has been only partially studied is their role in software engineering, and in particular their merit as a software architecture style. As we demonstrate, multi-agent systems developed to date have several common architectural characteristics, even though differences in their design and implementation result in variations in their strengths and weaknesses. A large portion of the research in the design and implementation of MAS addresses questions such as: given a computational problem---can one build a MAS to solve it? What should be the properties of this MAS given the problem? Having developed a MAS, what is the class of problems that this MAS, either as developed or with slight modifications, can solve? MAS research has provided several answers to the questions above. However, more fundamental questions were left un-answered: given a computational problem---is a MAS an appropriate solution? If it is, what type of MAS should be preferred? ..

Cooperative Goal-Satisfaction Without Communication in Large-Scale Agent-Systems

. A framework for cooperative goal-satisfaction in largescale environments is presented in this paper, focusing on a low complexity physics-oriented approach. The multi-agent systems with which we deal are modeled by a physics-oriented model. According to the model, agent-systems inherit physical properties, and therefore the evolution of the computational systems is similar to the evolution of physical systems. To enable implementation of the model, we provide a detailed algorithm to be used by a single agent within the system. The model and the algorithm are appropriate for large-scale Distributed Problem Solver systems, in which agents try to increase the benefits of the whole system. The complexity is very low, and in some specific cases it has proven to be optimal. The analysis and assessment of the algorithm are performed via the well-known behavior and properties of the physical system which models the computational system. 1 INTRODUCTION Multi-agent systems are designed in ord..

Coalition Formation Among Rational Information Agents

Information agents can be an important tool for information-gathering and queryanswering for the expanding WWW service as well as the large number of existing autonomous databases. Such agents behave like active intelligent front-ends of the standalone information systems. Information agents may work as individuals trying to satisfy thier own query-answering, i.e., a set of given information search tasks. However, they must cooperate efficiently with one another in order to gather information in non-local domains. In this paper we present an approach for cooperation and coalition formation among information agents for heterogeneous databases. In order to deal with the required association autonomy of these agents, we have developed a special decentralized coalition formation mechanism. It allows individually rational cooperation among the agents for information search. The semi-automatic creation of a local terminological information model enables each agent to hide local schema data a..

Task Allocation Via Coalition Formation Among Autonomous Agents

Autonomous agents working in multi-agent environments may need to cooperate in order to fulfill tasks. Given a set of agents and a set of tasks which they have to satisfy, we consider situations where each task should be attached to a group of agents which will perform the task. The allocation of tasks to groups of agents is necessary when tasks cannot be performed by a single agent. It may also be useful to assign groups of agents to tasks when the group's performance is more efficient than the performance of single agents. In this paper we give an efficient solution to the problem of task allocation among autonomous agents, and suggest that the agents will form coalitions in order to perform tasks or improve the efficiency. We present a distributed algorithm with a low ratio bound and with a low computational complexity. Our algorithm is an any-time algorithm, it is simple, efficient and easy to implement. 1 Introduction Autonomous agents working in multi-agent environments may need..