A multi-issue negotiation protocol among agents with nonlinear utility functions

Abstract

Multi-Issue Negotiation protocols have been studied very widely and represent a promising field since most of negotiation problems in the realworld are complex ones including multiple issues. In particular, in reality issues are constrained each other. This makes agents' utilities nonlinear. There have been a lot of work on multi-issue negotiations. However, there have been very few work that focus on nonlinear utility spaces. In this paper, we assume agents have nonlinear utility spaces. For the linear utility domain, agents can aggregate the utilities of the issue-values by simple linear summation. In the real world, such aggregations are unrealistic. For example, we cannot just add up the value of car's tires and the value of car's engine when engineers design a car. In this paper, we propose an auction-based multiple-issue negotiation protocol among nonlinear util-1 ity agents. Our negotiation protocol employs several techniques, i.e., adjusting sampling, auction-based maximization of social welfare. Our experimental results show that our method can outperform the existing simple methods in particular in the huge utility space that can be often found in the real-world. Further, theoretically, our negotiation protocol can guarantee the completeness if some conditions are satisfied.

From problems to protocols: Towards a negotiation handbook

“…The weighted hypercube approach (Ito et al, 2008) represents a utility function as a collection of hypercubes that each assigns a numeric weight to a sub-volume of the domain of possible contracts: utility_function := (ufun <weighted_hypercube>*) weighted_hypercube := (hypercube <weight> + <bound>*) bound := (<issue> <min value> <max value>)…”

“…Users can search the Negowiki scenario repository for scenarios with desired properties and download them in an XML format that instantiates the weighted hypervolume formalism described in section 2. The repository currently includes a range of scenarios drawn from the research literature, including (Faratin et al, 2000) (Klein et al, 2003) (Ito et al, 2008) (Lopez-Carmona et al, 2011. Users can search for scenarios based on their properties (figure 19): Users can also download function libraries (currently available in Matlab and Common Lisp) that calculate the utility of a given contract for a given scenario, making it straightforward for a research group to use the scenarios in their protocol evaluation experiments.…”

Mediated Heuristic Approaches and Alternative Social Welfare Definitions for Complex Contract Negotiations Involving Highly Uncorrelated Utility Spaces

“…However, most of these approaches rely on monotonic utility spaces, binary valued issues, low-order dependencies, a fixed set of defined apriorisolutions or simplification of the negotiation space, and there are very few works addressing auto-uncorrelated utility spaces with high-order issue interdependencies. One of the most relevant approaches in this field is (Ito et al, 2007). They propose a bidding mechanism, which is based on taking random samples of the contract space and applying simulated annealing to these samples to identify high utility regions for each agent, sending these regions as bids to a mediator, and then performing a search in the mediator to find overlaps between the bids of the different agents.…”

Acceptance Conditions in Automated Negotiation

“…A number of successful negotiation strategies have already been established both in literature and in implementations [5,6,11,12,19]. And more recently, in 2010 seven new negotiation strategies were created to participate in the first automated negotiating agents competition (ANAC 2010) [3] in conjunction with the Ninth International Conference on Autonomous Agents and Multiagent Systems (AAMAS-10).…”