Automated negotiation by software agents is a key enabling technology for agent mediated e-commerce. To this end, this paper considers an important class of such negotiations – namely those in which an agent engages in multiple concurrent bilateral negotiations for a good or service. In particular, we consider the situation in which a buyer agent is looking for a single service provider from a number of available ones in its environment. By bargaining simultaneously with these providers and interleaving partial agreements that it makes with them, a buyer can reach good deals in an efficient manner. However, a key problem in such encounters is managing commitments since an agent may want to make intermediate deals (so that it has a definite agreement) with other agents before it gets to finalize a deal at the end of the encounter. To do this effectively, however, the agents need to have a flexible model of commitments that they can reason about in order to determine when to commit and to decommit. This paper provides and evaluates such a commitment model and integrates it into a concurrent negotiation model.

Summary. This chapter discusses coordination from a commitment basis. Typically, commitments are established via a process of negotiation between the parties— the debtor and creditor—involved in the commitment. We define obligations to be those commitments, sometimes termed norms or social commitments, without a clearly identifiable creditor. The establishment of a commitment occurs in response to the adoption of a goal or the acceptance and performance of a task. Using a service-oriented computing (SOC) context, we describe an efficient negotiation process for establishing commitments. We then show how commitments and obligations can be used to monitor and control the aggregate behavior of a group of agents to yield coordinated progress towards the agents ’ overall objective. 1

Negotiating with suppliers and with customers is a key part of supply chain management. However, with recent technological advances, the mechanisms available to carry out such activities have become increasingly sophisticated, and the environment in which these activities take place has become highly dynamic. As a consequence, the overall planning of these complex trades, and the coordination of the various component activities, need to be carefully considered. In this setting, it is crucial that the intended behaviour, and through that, the desired outcomes, of these composite trading activities be expressed in a suitably precise manner. Using an approach based on the generation of negotiation plans, this paper describes (i) an approach to the specification of such complex activities, and (ii) a corresponding execution model. The proposal is illustrated and validated by means of a scenario taken from a recent trading agent competition.

Coalition formation in multi-agent systems is a process where agents form coalitions and work together to solve a joint problem via cooperating or coordinating their actions within each coalition. It is important for distributed applications ranging from electronic business to mobile and ubiquitous computing where adaptation to changing resources and environments is crucial. Coalition formation is useful as it may increase the ability of agents to accomplish tasks and achieve their goals. However, in complex real-world environments that agents operate in, the available resources are generally constrained. Agents only have incomplete even inaccurate information about the dynamically changing world. The occurrence of events may require the agents to react in a real-time manner. Agents’ actions may result in uncertain outcomes. These factors inevitably influence the formation process and formation outcome of a coalition. We employ a learning-based two-phased coalition formation approach to help agents form coalitions in complex environments. The approach consists of (1) a two-phase (planning and instantiation) coalition formation model, (2) a two-level (strategic and tactical) learning mechanism, (3) an adaptive, confidence-based negotiation strategy, and

This is to certify that the thesis entitled Distributed Algorithms for Hierarchical Area

Abstract—The allocation of resources to tasks in an efficient manner is a key problem in computer science. One important application domain for solutions to this class of problem is the allocation of sensor resources for military monitoring, surveillance, or similar sensing tasks. In such problem domains, the problem is compounded by the fact that the number of tasks and resources change over time, the number of available resources is limited and tasks compete for resources. Thus, it is necessary for a practical allocation mechanism to have the flexibility to cope with dynamic environments, and to ensure that unfair advantages are not given to a subset of the tasks (say, because they arrived first). Typical contemporary approaches use agents to manage individual resources, and the allocation problem is modeled as a coordination problem. In existing approaches, however, the successful allocation of resources to a new task is strongly dependent upon the allocation of resources to existing tasks. In this paper we propose a novel negotiation mechanism for exchanging resources to accommodate the arrival of new tasks, dynamically re-arranging the resource allocation. We have shown, via a set of experiments, that our approach offers significantly better results when compared with an agent-based approach without resource re-allocation through concurrent negotiation. I.

doi: 10.3233/WIA-2008-0143 Copyright © 2008 IOS Press. Used by permission. Investigating adaptive, confidence-based strategic negotiations in complex multiagent environments

Logistics service chains are characterized by multiple service providers contributing to the provision of a composite logistics service to a customer. In particular, various contractual dependencies exist across service chain levels. The object of our research is resource allocation which has to consider these dependencies to avoid overcommitment and overpurchasing. We propose a multi-tier negotiation protocol for solving this problem. The proposed artifact is developed from an interaction protocol engineering perspective in accordance with the design science paradigm. First evaluation experiments show that the protocol prevents overcommitments and overpurchasing, leading to higher expected profits for logistics service providers.