We present a generalized market architecture that provides support for a variety of types of transactions, from simple buying and selling of goods and services to complex multi-agent contract negotiations. This architecture is organized around three basic components: the exchange, the market, and the session. We also present a negotiation protocol for planning by contracting that takes advantage of the services of the market. We show how the existence of an appropriate market infrastructure can add value to a multi-agent contracting protocol by controlling fraud and discouraging counterspeculation.

Our research agenda focuses on building software agents that can facilitate and streamline group problem solving in organizations. We are particularly interested in developing intelligent agents that can partially automate routine information processing tasks by representing and reasoning with the preferences and biases of associated users. The distributed meeting scheduler is a collection of agents, responsible for scheduling meetings for their respective users. Users have preferences on when they like to meet, e.g. time of day, day of week, status of other invitees, topic of the meeting, etc. The agent must balance such concerns, proposing and accepting meeting times that satisfy as many of these criteria as possible. For example, a user might prefer not to meet at lunchtime unless the president of the company is hosting the meeting. We apply techniques from voting theory to arrive at consensus choices for meeting times while balancing different preferences. 1 Introduction Routine...

The theory of mechanism design deals with the design of protocols for non-cooperative multi-agent systems. A major task of this theory is the design of protocols that will maximize the social welfare of the agents. An ideal mechanism will optimize social welfare and will be strategy-proof, i.e. the dominant strategy of each agent will be to participate in the mechanism and to reveal his true goal and worth, as well as budget-balanced, i.e., the mechanism should not impose any payments from the center/organizer to the agents. Indeed, the Clarke's mechanism, which is central to information economics and to games with incomplete information satisfies these properties. However, we show that the Clarke's mechanism employs the use of procedures for optimizing social welfare, which are NP-hard. Hence, these procedures should be replaced by heuristics. We present a set of natural properties (axioms) of such heuristics that, when satisfied, enable to obtain the desired strategy-proofness and bu...

We present a system for multi-agent contract negotiation, implemented as a generalized market architecture called MAGNET. MAGNET provides support for a variety oftypes of transactions, from simple buying and selling of goods and services to complex multi-agent contract negotiations. In the latter case, MAGNET is designed to negotiate contracts based on temporal and precedence constraints, and includes facilities for dealing with time-based contingencies. In contrast with other approaches to multi-agent negotiation, we introduce an explicit intermediary into the negotiation process, which helps in controlling fraud and discouraging counterspeculation.

Abstract—Two processes are necessary to solve group decision making problems: A consensus process and a selection process. The consensus reaching process is necessary to obtain a final solution with a certain level of agreement between the experts; and the selection process is necessary to obtain such a final solution. In a previous paper, we present a selection process to deal with group decision making problems with incomplete fuzzy preference relations, which uses consistency measures to estimate the incomplete fuzzy preference relations. In this paper we present a consensus model. The main novelty of this consensus model is that of being guided by both consensus and consistency measures. Also, the consensus reaching process is guided automatically, without moderator, through both consensus and consistency criteria. To do that, a feedback mechanism is developed to generate advice on how experts should change or complete their preferences in order to reach a solution with high consensus and consistency degrees. In each consensus round, experts are given information on how to change their preferences, and to estimate missing values if their corresponding preference relation is incomplete. Additionally, a consensus and consistency based induced ordered weighted averaging operator to aggregate the experts ’ preferences is introduced, which can be used in consensus models as well as in selection processes. The main improvements of this consensus model is that it supports the management of incomplete information and it allows to achieve consistent solutions with a great level of agreement. Index Terms—Aggregation, consensus, fuzzy preference relations, group decision making (GDM). I.

As distributed systems of computers play an increasingly important role in society, it will be necessary to consider ways in which these machines can be made to interact effectively. Especially when the interacting machines have been independently designed, it is essential that the interaction environment be conducive to the aims of their designers. These designers might, for example, wish their machines to behave efficiently, and with a minimum of overhead required by the coordination mechanism itself. The rules of interaction should satisfy these needs, and others. Formal tools and analysis can help in the appropriate design of these rules.

In an automated contracting environment, where a \customer" agent must negotiate with other self-interested \supplier " agents in order to execute its plans, there is a tradeo between giving the suppliers su cient exibility to incorporate the requirements of the customer's call-for-bids into their own resource schedules, and ensuring the customer that any bids received can be composed into a feasible plan. In this paper, we introduce a bid evaluation process that incorporates cost, task coverage, temporal feasibility, and risk estimation. Using this evaluation process, we provide an empirical study of the tradeo s between exibility, plan feasibility, and cost in the context of our MAGNET multi-agent contracting market infrastructure. Our experimental results demonstrate that the advantage of increasing supplier exibility is dependent on the number of available suppliers. In other words, if the number of suppliers is small, the risk of plan infeasibility outweighs the advantage of added exibility. On the other hand, if the number of suppliers is large, the more exible plan speci cations result in lower-risk plans. 1 1

Different consensus models for group decision-making (GDM) problems have been proposed in the literature. However, all of them consider the consensus reaching process a rigid or inflexible one because its behavior remains fixed in all rounds of the consensus process. The aim of this paper is to improve the consensus reaching process in GDM problems defined in multigranular linguistic contexts, i.e., by using linguistic term sets with different cardinality to represent experts’ preferences. To do that, we propose an adaptive consensus support system model for this type of decision-making problem, i.e., a process that adapts its behavior to the agreement achieved in each round. This adaptive model increases the convergence toward the consensus and, therefore, reduces the number of rounds to reach it.

Social Networking is one of the major technological phenomena of the Web 2.0, with hundreds of millions of people participating. Social networks enable a form of self expression for users, and help them to socialize and share content with other users. In spite of the fact that content sharing represents one of the prominent features of existing Social Network sites, Social Networks yet do not support any mechanism for collaborative management of privacy settings for shared content. In this paper, we model the problem of collaborative enforcement of privacy policies on shared data by using game theory. In particular, we propose a solution that offers automated ways to share images based on an extended notion of content ownership. Building upon the Clarke-Tax mechanism, we describe a simple mechanism that promotes truthfulness, and that rewards users who promote co-ownership. We integrate our design with inference techniques that free the users from the burden of manually selecting privacy preferences for each picture. To the best of our knowledge this is the first time such a protection mechanism for Social Networking has been proposed. In the paper, we also show a proof-of-concept application, which we implemented in the context of Facebook, one of today’s most popular social networks. We show that supporting these type of solutions is not also feasible, but can be implemented through a minimal increase in overhead to end-users.

In this paper, we consider the problem of data allocation in environments of selfmotivated servers, where information servers respond to queries from users. New data items arrive frequently and have to be allocated in the distributed system. The servers have no common interests, and each server is concerned with the exact location of each of the data items. There is also no central controller. We suggest using a negotiation framework which takes into account the passage of time during the negotiation process itself. Using this negotiation mechanism, the servers have simple and stable negotiation strategies that result in efficient agreements without delays. We provide heuristics for finding the details of the strategies which depend on the specific settings of the environment and which cannot be provided to the agents in advance. We demonstrate the quality of the heuristics, using simulations. We consider situations characterized by complete, as well as incomplete, informati...