SPECIFYING AND VERIFYING COMPLIANCE IN COMMITMENT PROTOCOLS BY

ment Protocols (Under the direction of Dr. Munindar P. Singh). Interaction protocols are specific, often standard, constraints on the behaviors of au-tonomous agents in a multiagent system. Protocols are essential to the functioning of open systems, such as those that arise in most interesting web applications. A variety of common protocols in negotiation and electronic commerce are best treated as commitment protocols, which may be defined and analyzed in terms of the creation, satisfaction, or manipulation of the commitments among the participating agents. When protocols are employed in open environments, such as the Internet, they must be executed by agents that behave more or less autonomously and whose internal designs are not known. In such settings, therefore, there is a risk that the participating agents may fail to comply with the given protocol. Without a rigorous means to verify compliance, the very idea of protocols for interoperation is subverted. We develop an approach for verifying whether the behavior of an agent complies with a given commitment protocol. Our approach requires the specification of commitment protocols in temporal logic, and involves a novel way of synthesizing and applying ideas from distributed computing and logics of program

Verifying Compliance with Commitment Protocols

Interaction protocols are specific, often standard, constraints on the behaviors of the autonomous agents in a multiagent system. Protocols are essential to the functioning of open systems, such as those that arise in most interesting web applications. A variety of common protocols in negotiation and electronic commerce are best treated as commitment protocols, which are defined, or at least analyzed, in terms of the creation, satisfaction, or manipulation of the commitments of the various agents to one another. When protocols are employed in open environments, such as the Internet, they must be executed by agents that behave more or less autonomously and whose internal designs are not known. In such settings, therefore, there is a risk that the participating agents may fail to comply with the protocol. Without a rigorous means to verify compliance, the very idea of protocols for interoperation is subverted. We develop a novel approach for testing the compliance of agents with respect ..

Verifying compliance with commitment protocols: Enabling open web-based multiagent systems

Abstract. Interaction protocols are specific, often standard, constraints on the behaviors of autonomous agents in a multiagent system. Protocols are essential to the functioning of open systems, such as those that arise in most interesting web applications. A variety of common protocols in negotiation and electronic commerce are best treated as commitment protocols, which are defined, or at least analyzed, in terms of the creation, satisfaction, or manipulation of the commitments among the participating agents. When protocols are employed in open environments, such as the Internet, they must be executed by agents that behave more or less autonomously and whose internal designs are not known. In such settings, therefore, there is a risk that the participating agents may fail to comply with the given protocol. Without a rigorous means to verify compliance, the very idea of protocols for interoperation is subverted. We develop an approach for testing whether the behavior of an agent complies with a commitment protocol. Our approach requires the specification of commitment protocols in temporal logic, and involves a novel way of synthesizing and applying ideas from distributed computing and logics of program

A Multiagent Referral System for Expertise Location

A referral system is an agent-based framework for assisting and simplifying person-to-person communication, such as finding experts for a specified topic. The informal person-to-person social networks are used as "referral chain" requests for expertise, and software agents help automate the search of information and expertise. However, current systems rely exclusively on collections of email messages or newsgroup postings. As a result, previous approaches yield poor referrals for requests outside of the domain of the given collection. By contrast, we develop an approach that (1) combines techniques from information retrieval, multiagent learning and adaptive user modeling to refine the social network according to the user's needs, and (2) allows agents to unintrusively exchange explicit profile information to add coverage regarding a user's expertise. An experimental simulation has been implemented and results of its use are presented

Verifying Compliance with Commitment Protocols

Interaction protocols are specific, often standard, constraints on the behaviors of autonomous agents in a multiagent system. Protocols are essential to the functioning of open systems, such as those that arise in most interesting web applications. A variety of common protocols in negotiation and electronic commerce are best treated as commitment protocols, which are defined, or at least analyzed, in terms of the creation, satisfaction, or manipulation of the commitments among the participating agents

An Adaptive Social Network for Information Access:

We consider a social network of software agents who assist each other in helping their users find information. Unlike in most previous approaches, our architecture is fully distributed and includes agents who preserve the privacy and autonomy of their users. These agents learn models of each other in terms of expertise (ability to produce correct domain answers) and sociability (ability to produce accurate referrals). We study our framework experimentally to study how the social network evolves. Specifically, we find that under our multiagent learning heuristic, the quality of the network improves with interactions; the quality is maximized when both expertise and sociability are considered; pivot agents further improve the quality of the network and have a catalytic effect on its quality even if they are ultimately removed. Moreover, the quality of the network improves when clustering decreases, reflecting the intuition that you need to talk to people outside your close circle to get the best information