Automated Service Negotiation Between Autonomous Computational Agents

PhDMulti-agent systems are a new computational approach for solving real world, dynamic and open system problems. Problems are conceptualized as a collection of decentralised autonomous agents that collaborate to reach the overall solution. Because of the agents autonomy, their limited rationality, and the distributed nature of most real world problems, the key issue in multi-agent system research is how to model interactions between agents. Negotiation models have emerged as suitable candidates to solve this interaction problem due to their decentralised nature, emphasis on mutual selection of an action, and the prevalence of negotiation in real social systems. The central problem addressed in this thesis is the design and engineering of a negotiation model for autonomous agents for sharing tasks and/or resources. To solve this problem a negotiation protocol and a set of deliberation mechanisms are presented which together coordinate the actions of a multiple agent system. In more detail, the negotiation protocol constrains the action selection problem solving of the agents through the use of normative rules of interaction. These rules temporally order, according to the agents' roles, communication utterances by specifying both who can say what, as well as when. Specifically, the presented protocol is a repeated, sequential model where offers are iteratively exchanged. Under this protocol, agents are assumed to be fully committed to their utterances and utterances are private between the two agents. The protocol is distributed, symmetric, supports bi and/or multi-agent negotiation as well as distributive and integrative negotiation. In addition to coordinating the agent interactions through normative rules, a set of mechanisms are presented that coordinate the deliberation process of the agents during the ongoing negotiation. Whereas the protocol normatively describes the orderings of actions, the mechanisms describe the possible set of agent strategies in using the protocol. These strategies are captured by a negotiation architecture that is composed of responsive and deliberative decision mechanisms. Decision making with the former mechanism is based on a linear combination of simple functions called tactics, which manipulate the utility of deals. The latter mechanisms are subdivided into trade-off and issue manipulation mechanisms. The trade-off mechanism generates offers that manipulate the value, rather than the overall utility, of the offer. The issue manipulation mechanism aims to increase the likelihood of an agreement by adding and removing issues into the negotiation set. When taken together, these mechanisms represent a continuum of possible decision making capabilities: ranging from behaviours that exhibit greater awareness of environmental resources and less to solution quality, to behaviours that attempt to acquire a given solution quality independently of the resource consumption. The protocol and mechanisms are empirically evaluated and have been applied to real world task distribution problems in the domains of business process management and telecommunication management. The main contribution and novelty of this research are: i) a domain independent computational model of negotiation that agents can use to support a wide variety of decision making strategies, ii) an empirical evaluation of the negotiation model for a given agent architecture in a number of different negotiation environments, and iii) the application of the developed model to a number of target domains. An increased strategy set is needed because the developed protocol is less restrictive and less constrained than the traditional ones, thus supporting development of strategic interaction models that belong more to open systems. Furthermore, because of the combination of the large number of environmental possibilities and the size of the set of possible strategies, the model has been empirically investigated to evaluate the success of strategies in different environments. These experiments have facilitated the development of general guidelines that can be used by designers interested in developing strategic negotiating agents. The developed model is grounded from the requirement considerations from both the business process management and telecommunication application domains. It has also been successfully applied to five other real world scenarios

The Growing Complexity of Internet Interconnection

End-to-End (E2E) packet delivery in the Internet is achieved through a system of interconnections between heterogeneous entities called Autonomous Systems (ASes). The initial pattern of AS interconnection in the Internet was relatively simple, involving mainly ISPs with a balanced mixture of inbound and outbound traffic. Changing market conditions and industrial organization of the Internet have jointly forced interconnections and associated contracts to become significantly more diverse and complex. The diversity of interconnection contracts is significant because efficient allocation of costs and revenues across the Internet value chain impacts the profitability of the industry. Not surprisingly, the challenges of recovering the fixed and usage-sensitive costs of network transport give rise to more complex settlements mechanisms than the simple bifurcated (transit and peering) model described in many earlier analyses of Internet interconnection (see BESEN et al., 2001; GREENSTEIN, 2005; or LAFFONT et al., 2003). In the following, we provide insight into recent operational developments, explaining why interconnection in the Internet has become more complex, the nature of interconnection bargaining processes, the implications for cost/revenue allocation and hence interconnection incentives, and what this means for public policy. This paper offers an abbreviated version of the original paper (see FARATIN et al., 2007b).internet interconnection, economics, public policy, routing, peering.

General Terms Algorithms

Work to date on computational models of negotiation has focused almost exclusively on defining contracts consisting of one or a few independent issues. Many real-world contracts, by contrast, consist of multiple inter-dependent issues. This paper describes a simulated annealing based approach appropriate for negotiating such complex contracts, evaluates its efficacy, and suggests potentially promising avenues for future work

Negotiation decision functions for autonomous agents

We present a formal model of negotiation between autonomous agents. The purpose of the negotiation is to reach an agreement about the provision of a service by one agent for another. The model defines a range of strategies and tactics that agents can employ to generate initial offers, evaluate proposals and offer counter proposals. The model is based on computationally tractable assumptions, demonstrated in the domain of business process management and empirically evaluated. © 1998 Elsevier Science B.V. All rights reserved.This project has received the support of the DTI/EPSRC Intelligent Systems Integration Programme (ISIP) project ADEPT, Nortel Technology and the Spanish Research project SMASH (CICYT number, TIC96-1038-C04001). With the support of the Spanish Ministry of Education grant PR95-313.Peer Reviewe

Using similarity criteria to make issue trade-offs in automated negotiations

Automated negotiation is a key form of interaction in systems that are composed of multiple autonomous agents. The aim of such interactions is to reach agreements through an iterative process of making offers. The content of such proposals are, however, a function of the strategy of the agents. Here we present a strategy called the trade-off strategy where multiple negotiation decision variables are traded-off against one another (e.g., paying a higher price in order to obtain an earlier delivery date or waiting longer in order to obtain a higher quality service). Such a strategy is commonly known to increase the social welfare of agents. Yet, to date, most computational work in this area has ignored the issue of trade-offs, instead aiming to increase social welfare through mechanism design. The aim of this paper is to develop a heuristic computational model of the trade-off strategy and show that it can lead to an increased social welfare of the system. A novel linear algorithm is presented that enables software agents to make trade-offs for multi-dimensional goods for the problem of distributed resource allocation. Our algorithm is motivated by a number of real-world negotiation applications that we have developed and can operate in the presence of varying degrees of uncertainty. Moreover, we show that on average the total time used by the algorithm is linearly proportional to the number of negotiation issues under consideration. This formal analysis is complemented by an empirical evaluation that highlights the operational effectiveness of the algorithm in a range of negotiation scenarios. The algorithm itself operates by using the notion of fuzzy similarity to approximate the preference structure of the other negotiator and then uses a hill-climbing technique to explore the space of possible trade-offs for the one that is most likely to be acceptable. © 2002 Elsevier Science B.V. All rights reserved.This line of research is currently being supported by the MCYT research project eINSTITUTOR (TIC2000-1414).Peer Reviewe