Negotiation In Multi-Agent Systems

PhD Thesis, 2013

Multi-agent systems (MAS) are distributed systems where autonomous entities called agents, either human or software, pursue their own goals. The MAS paradigm has been proposed as the appropriate modeling approach for the deployment of applications like electronic commerce, multi-robot systems, security applications, and so forth. In the MAS community, the vision of open multi-agent system, where heterogeneous agents can enter and leave the system dynamically, has gained strength as a potentially interesting modeling paradigm due to its conceptual relation with technologies like world wide web, grid computing, and virtual organizations. Given the heterogeneity and agent's self-interest, conflict is a candidate phenomenon to arise in multi-agent systems. In the last few years, the term agreement technologies has been used to address all the mechanisms that, directly or indirectly, promote the resolution of conflicts in computational systems like multi-agent systems. Among agreement technologies, automated negotiation is proposed as one key mechanism in conflict resolution due to its analogous use in human conflict resolution. Automated negotiation consists of an automated exchange of proposals carried out by software agents on behalf of their users. The final goal is the achievement of an agreement with all the involved parts. Despite being studied by scholars in Artificial Intelligence for several years, several problems have not been addressed by the scientific community yet. The main objective of this thesis is proposing negotiation models for complex scenarios where the complexity may stem from (i) limited computational capabilities or (ii) the necessity to accommodate the preferences of multiple individuales. In the first part of the thesis we propose a bilateral negotiation model for the problem of negotiation in Ambient Intelligence (AmI), a domain with a special emphasis on computational efficiency due to the limited capability of AmI devices. In the second part of the thesis we propose several negotiation models for agent-based negotiation teams. A negotiation team is a group of individuals that acts together as single negotiation party due to its common interests in the negotiation at hand. The complexity of negotiation teams resides in the fact that despite having common interests, intra-team conflict is also present. As far as we are concerned, the topic of negotiation teams in MAS is introduced with this thesis.

2018

In this chapter we elaborate on the specification and exploitation of a software agent-based Electronic Institution, embedding both a Normative Environment and a Computational Trust service which, when used in tandem, lead to an enhanced process of selection of potential business partners and enable automatic contract negotiation. We introduce a formalization of a Normative Environment, which accommodates the establishment of e-contracts and provides a contract monitoring facility. Contracts are established and enacted by contractual partners previously selected through an automatic negotiation process. While monitoring contracts at run-time, the Normative Environment makes use of a reporting mechanism to inform relevant contract enactment events to interested parties. In our work, we benefit from this reporting function by exploiting it as an input to a computational trust mechanism. We also present the built-in Computational Trust service, a key element of the Electronic Instituti...

Multi-agent systems and applications, 2006

This paper presents some of the key techniques for reaching agreements in multi-agent environments. It discusses game-theory and economics based techniques: strategic negotiation, auctions, coalition formation, market-oriented programming and contracting. It also presents logical based mechanisms for argumentations. The focus of the survey is on negotiation of self-interested agents, but several mechanisms for cooperative agents who need to resolve conflicts that arise from conflicting beliefs about different aspects of their environment are also mentioned. For space reasons, we couldn't cover all the relevant works, and the papers that are mentioned only demonstrate the possible approaches. We present some of the properties of the approaches using our own previous work.

2014

Argumentation-based negotiation (ABN) is a prevailing approach for automated negotiation. It is based on the exchange of arguments that allow an agent to acquire additional information about the other agents and the particular circumstances of the negotiation, and can be used for attacking or justifying offers. This is an important element in resolving conflicts that very often are due to the assumptions agents have made when making decisions and which may be found to be false in the course of the negotiation. Argumentation-based negotiation can be characterized in terms of three main topics, namely a) the reasoning mechanisms the agents use for negotiating and which are based on argumentation, b) the protocols the agents use for conveying arguments and offers and, c) the strategies that determine their choices at each step of the negotiation. This chapter presents argumentationbased negotiation by discussing representative works dealing with these three topics.

Proceeding

The increasing demand for distributed entities to interact in complex domains necessitates the need for cooperation, coordination and negotiation to reach agreement. Examples of such systems are: the flow of work and information through cooperating companies (virtual enterprises), international air traffic controllers, the coordination of logistic processes in shipping companies, the use of flexible transport systems in industrial manufacturing and assembly, and the operation of multi-guidance and control systems. This paper describes the design of a model that uses a hierarchy of negotiation protocols to solve conflicts in any of the INTERRAP layers. Two testbeds have been developed to test the proposed hierarchical model: a Desktop Configuration and a Travel Planning Domains. The testbeds proved the effectivness of the model in solving conflicts among several agents in all the INTERRAP layers. These two domains have been chosen because they introduce various types of conflictswhich could be solved using various negotiation protocols in the model.