A negotiation framework for linked combinatorial optimization problems

Duan, Lei; Doğru, Mustafa K.; Özen, Ulaş; Beck, J. Christopher

doi:10.1007/s10458-011-9172-7

Cited by 20 publications

(10 citation statements)

References 13 publications

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“…Each negotiation is organised in three main steps: initialisation; refinement of the job under negotiation; and closure. The initialisation step allows to define what has to be negotiated (Negotiation Object) and how (Negotiation Framework) [36]. In the refinement step, participants exchange proposals on the negotiation object trying to satisfy their constraints.…”

Section: Sustainability and Interoperability Of Negotiation Processesmentioning

confidence: 99%

Sustainability and Interoperability: Two Facets of the Same Gold Medal

Dassisti

Jardim-Goncalves

Molina

et al. 2013

Lecture Notes in Computer Science

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To sustain is to endure' -that is, to be able to survive and continue to function in the face of significant changes. The commonly accepted concept of 'sustainability' currently encompasses three main pillars: environmental, social/ethical and economic. In a metaphor of survival, they can be seen as water, food and air; one needs all three, only with varying degrees of urgency. In today's globally networked environment, it is becoming obvious that one cannot achieve environmental, social or economic sustainability of any artefact (be it physical or virtual, e.g. enterprise, project, information system, policy, etc) without achieving ubiquitous ability of the artefact and its creators and users to exchange and understand shared information and if necessary perform processes on behalf of each other -capabilities that are usually defined as 'interoperability'. Thus, sustainability relies on interoperability, while, conversely, interoperability as an ongoing concern relies for its existence on all three main pillars of sustainability. This paper aims to test the hypothesis that interoperability and sustainability are two inseparable and inherently linked aspects of any universe of discourse. To achieve this, it applies the dualistic sustainability / interoperability viewpoint to a variety of areas (manufacturing, healthcare, information and communication technology and standardisation), analyses the results and synthesizes conclusions and guidelines for future work.

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Section: Sustainability and Interoperability Of Negotiation Processesmentioning

confidence: 99%

Sustainability and Interoperability: Two Facets of the Same Gold Medal

Dassisti

Jardim-Goncalves

Molina

et al. 2013

Lecture Notes in Computer Science

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“…There are also recent papers in the artificial intelligence literature that, like ours, focus on "non-equilibrium solution concepts" (Brafman & Tennenholtz, 2003;Rezek, Leslie, Reece, Roberts, Rogers, Dash, & Jennings, 2008;Aydogan & Yolum, 2012;Duan, Dogru,Özen, & Beck, 2012). Rather than merely invoking equilibrium, Brafman and Tennenholtz (2003) employ a reinforcement learning algorithm to efficiently achieve coordination in common interest stochastic games.…”

Section: Introductionmentioning

confidence: 95%

“…they assume players make inferences about their opponents in a Bayesian framework and derive a novel fictitious play algorithm. Recent work in AI that focuses on bargaining, such as that of Aydogan and Yolum (2012) and Duan et al (2012), is particularly closely related to the current paper. The main difference is that our paper focuses on an unstructured game, whereas the focus in previous work has been on structured games.…”

Section: Introductionmentioning

confidence: 99%

Predicting Behavior in Unstructured Bargaining with a Probability Distribution

Wolpert¹,

Bono²

2013

jair

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In experimental tests of human behavior in unstructured bargaining games, typically many joint utility outcomes are found to occur, not just one. This suggests we predict the outcome of such a game as a probability distribution. This is in contrast to what is conventionally done (e.g, in the Nash bargaining solution), which is predict a single outcome. We show how to translate Nash's bargaining axioms to provide a distribution over outcomes rather than a single outcome. We then prove that a subset of those axioms forces the distribution over utility outcomes to be a power-law distribution. Unlike Nash's original result, our result holds even if the feasible set is finite. When the feasible set is convex and comprehensive, the mode of the power law distribution is the Harsanyi bargaining solution, and if we require symmetry it is the Nash bargaining solution. However, in general these modes of the joint utility distribution are not the experimentalist's Bayesoptimal predictions for the joint utility. Nor are the bargains corresponding to the modes of those joint utility distributions the modes of the distribution over bargains in general, since more than one bargain may result in the same joint utility. After introducing distributional bargaining solution concepts, we show how an external regulator can use them to optimally design an unstructured bargaining scenario. Throughout we demonstrate our analysis in computational experiments involving flight rerouting negotiations in the National Airspace System. We emphasize that while our results are formulated for unstructured bargaining, they can also be used to make predictions for noncooperative games where the modeler knows the utility functions of the players over possible outcomes of the game, but does not know the move spaces the players use to determine those outcomes.

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“…Problems of this type are the focus of many research studies every year [1,2]. Some classic examples of such problems are the Traveling Salesman Problem (TSP) [3], the Capacitated Vehicle Routing Problem [4], or the Job-shop Scheduling Problem [5].…”

Section: Introductionmentioning

confidence: 99%

On the influence of using initialization functions on genetic algorithms solving combinatorial optimization problems: A first study on the TSP

Osaba

Carballedo

Díaz

et al. 2014

2014 IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS)

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Combinatorial optimization is a widely studied field within artificial intelligence. There are many problems of this type, and many techniques applied to them can be found in the literature. Especially, population techniques have received much attention in this area, being genetic algorithms (GA) the most famous ones. Although throughout history many studies on GAs have been performed, there is still no study like the presented in this work. In this paper, a study on the influence of using heuristic initialization functions in genetic algorithms (GA) applied to combinatorial optimization problems is performed. Being the first phase of this research, the study is conducted using one of the best known problems in combinatorial optimization: the traveling salesman problem. Three different experimentations are carried out, using three different heuristic initialization functions. Additionally, for each experiment four versions of a GA have been developed for the comparison. Each of these variant differs in the initialization phase. The results obtained by each GA are compared to determine the influence of the use of heuristic functions for the initialization of the population.

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A negotiation framework for linked combinatorial optimization problems

Cited by 20 publications

References 13 publications

Sustainability and Interoperability: Two Facets of the Same Gold Medal

Sustainability and Interoperability: Two Facets of the Same Gold Medal

Predicting Behavior in Unstructured Bargaining with a Probability Distribution

On the influence of using initialization functions on genetic algorithms solving combinatorial optimization problems: A first study on the TSP

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