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Proceedings Article

Efficiency and Fairness in Air Traffic Control

01 Jan 2005-pp 151-157

AbstractAir Traffic Control Planning is a complex area of research in which there is a great need for new and efficient coordination techniques. The tight connection between several parties with different interests makes it a typical and challenging area for the application of multiagent techniques. We study the relation between two important underlying principles in airport traffic planning, namely utility and fairness. We model the problem as a multiagent resource allocation problem and show how one can improve on global utility and fairness if planning history is involved. We introduce three techniques using history and evaluate their performance by experiments.

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Citations
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Patent
24 May 2013
Abstract: This disclosure is concerned with a method of detecting conflicts between aircraft passing through managed airspace, and to resolving the detected conflicts strategically. The method may include obtaining intended trajectories of aircraft through the airspace, detecting conflicts in the intended trajectories, forming a set of the conflicted aircraft, calculating one or more revised trajectories for the conflicted aircraft such that the conflicts are resolved, and advising the conflicted aircraft subject to revised trajectories of the revised trajectories.

37 citations


Proceedings ArticleDOI
08 May 2006
TL;DR: This paper discusses a number of methodological issues raised by this study, pertaining in particular to the design of suitable payment functions as a means of distributing the social surplus generated by a deal amongst the participating agents.
Abstract: Notions of fairness have recently received increased attention in the context of resource allocation problems, pushed by diverse applications where not only pure utilitarian efficiency is sought. In this paper, we study a framework where allocations of goods result from distributed negotiation conducted by autonomous agents implementing very simple deals. Assuming that these agents are strictly self-interested, we investigate how equitable the outcomes of such negotiation processes are. We first discuss a number of methodological issues raised by this study, pertaining in particular to the design of suitable payment functions as a means of distributing the social surplus generated by a deal amongst the participating agents. By running different experiments, we finally identify conditions favouring equitable outcomes.

24 citations


Proceedings ArticleDOI
14 May 2007
TL;DR: A monetary system in which every user can issue money and every user is required to sign each credit it issues or circulates is presented, by using a trust-based credit-valuation function.
Abstract: We present a monetary system by which selfish agents can cooperate reciprocally. We show that a straight-forward market mechanism can lead to unfair situations when agents misuse key positions. We show that it is not easy to retaliate wrongdoers, as there is a dominant strategy that deviates from the retaliating strategy. We present a monetary system in which every user can issue money and every user is required to sign each credit it issues or circulates. By using a trust-based credit-valuation function, wrongdoers are retaliated and it is no longer dominant to deviate from the retaliating strategy.

15 citations


Proceedings ArticleDOI
21 Sep 2009
Abstract: The focus of the work presented in this paper is set on defining a framework and the corresponding process to develop a fairness and an equity metric for a given cost model. This paper provides a definition for a just framework in ATM as well as the definition of t he concept of fairness and equity in T rajectory B ased Operations. Two metrics are proposed, one for evaluating fairness and one for evaluating equity , based on an example for a cost index base d cost model .

8 citations


Dissertation
04 Feb 2010
TL;DR: This dissertation explores the issue of achieving long-term fair policies among multiple agents, and proposes a multi-objective genetic algorithm for finding good tradeoff points between beneficiaries utilities and their worst-case losses, and introduces a family of approximation algorithms.
Abstract: COMPUTATIONAL ISSUES IN LONG-TERM FAIRNESS AMONG GROUPS OF AGENTS Gabriel Catalin Balan, PhD George Mason University, 2009 Dissertation Director: Dr. Sean Luke Fairness within groups is important to a very broad range of problems, from policies for battery-operated soccer robots to distributed traffic control. While no single action may be fair to everyone, it is possible to achieve long-term optimal fairness for everyone through choice of repeated actions. I explore the issue of achieving such long-term fairness among multiple agents, and provide a unified view of the problem and solutions to it. The issue of constructing long-term fair policies among multiple agents has not been well studied in the literature. I concentrate on the “average reward” utility model, where one’s utility is defined as the average of the rewards one has received from past interactions. Also, I focus on a particular definition of fairness, called “leximin” fairness, but most of the results apply to other measures as well. After examination of fairness through an infinite series of repeated actions, I extend analysis in several directions. First, I consider how to achieve as fair a result as possible given a finite series of actions, where the length of the series is not precisely known beforehand but rather is chosen from an unknown or stochastic distribution of time horizons. My solution guarantees the beneficiaries the fairest possible long-term results, minus a bounded worst-case loss due to the game ending unexpectedly. I show that finding sequences of actions with optimal worst-case loss is NP-hard, and I propose a family of approximation algorithms. Second, I examine stateful domains, where one’s choices have side-effects that influence the effects of actions in the future. I introduce a multi-objective genetic algorithm for finding good tradeoff points between beneficiaries utilities and their worst-case losses. Third, I focus on decision-making processes which have been decentralized in the form of hierarchies. I propose an algorithm based on my stochastic time-horizon solution, and show empirically that an agent hierarchy running that algorithm is able to achieve optimal long-term utilities. Chapter 1: Introduction Multi-agent systems (MAS), the study and engineering of complex phenomena emergent from interacting agents, is becoming increasingly important, propelled by several different forces. One force comes from the field of pervasive computing: all of our appliances must work together to offer the best customized experience, regardless of their brand/manufacturer. The field of robotics provides another motivational force: while a huge mining robot might be preferable to several smaller ones, a large number of slow, coordinating robots are very likely to outperform a single faster robot in a surveillance task. The multi-agent approach offers robustness and modularity, which is important since a team of robots must gracefully handle robots joining the team or breaking down. Yet another reason is that people interact more and more through virtual media (auctions, IM, online-gaming, etc.) and the agents acting on behalf of these people need to display intelligence and even some autonomy in their interactions among themselves. Some modern multi-agent systems require fairness in addition to efficiency. Fairness is a highly desirable feature in applications where agents (e.g. web-browsers, email clients, etc) act on behalf of different people and must share some scarce resources (CPU cycles, bandwidth, etc). Alternatively, there are applications where fairness is not germane, but their measure of efficiency can be cast as a fairness measure. Specifically, goals such as network security and full network connectivity abide by the motto “a chain is only as strong as its weakest link,” which coincides with the maximin fairness concept: “a society’s measure of fairness is how it treats its poorest individual.” Another example is finding robust solutions when dealing with uncertainty in a single-agent setup: a course of actions can have one of several outcomes depending on an unknown state of the world, and bad

5 citations


References
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Journal Article
TL;DR: A survey of some of the most salient issues in Multiagent Resource Allocation, including various languages to represent the pref-erences of agents over alternative allocations of resources as well as different measures of social welfare to assess the overall quality of an allocation.
Abstract: Issues in Multiagent Resource Allocation Yann Chevaleyre, Paul E. Dunne, Ulle Endriss, Jerome Lang, Michel Lemaitre, Nicolas Maudet, Julian Padget, Steve Phelps, Juan A. Rodrigues-Aguilar, Paulo Sousa Abstract: The allocation of resources within a system of autonomous agents, that not only have preferences over alternative allocations of resources but also actively participate in computing an allocation, is an exciting area of research at the interface of Computer Science and Economics. This paper is a survey of some of the most salient issues in Multiagent Resource Allocation. In particular, we review various languages to represent the preferences of agents over alternative allocations of resources as well as different measures of social welfare to assess the overall quality of an allocation. We also discuss pertinent issues regarding allocation procedures and present important complexity results. Our presentation of theoretical issues is complemented by a discussion of software packages for the simulation of agent-based market places. We also introduce four major application areas for Multiagent Resource Allocation, namely industrial procurement, sharing of satellite resources, manufacturing control, and grid computing.

451 citations


Journal ArticleDOI
Abstract: We consider a simple production model and assume that the agents have unequal production skills that can in no way be considered their responsibility. We study how it is possible, if at all, to compensate for differential skills while holding agents responsible for their preferences towards consumption and leisure. Our main result is a characterization of a class of solutions, called the Reference Welfare Equivalent Budget. In this class, each solution is based on reference preferences, and selects allocations in which the agents' budget sets are deemed equivalent by these reference preferences.

94 citations


Book ChapterDOI
01 Jan 2001
Abstract: Collaborative Decision Making (CDM) embodies a new philosophy for managing air traffic. The initial implementation of CDM in the US has been aimed at Ground Delay Program Enhancements (GDP-E). However, the underlying concepts of CDM have the potential for much broader applicability. This paper reviews on-going and proposed CDM research streams. The topic areas discussed include: ground delay program enhancements; collaborative routing; performance monitoring and analysis; collaborative resource allocation mechanisms; game theory models for analyzing CDM procedures and information exchange; collaborative information collection and distribution.

89 citations


01 Jan 2000
TL;DR: It is shown that CDM has had a positive impact on the quality of information and its distribution through increased accuracy of flight departures and the submission of more timely flight cancellation notices.
Abstract: Collaborative Decision Making (CDM) embodies a new philosophy for managing air traffic. The initial implementation of CDM within the US, has been aimed at Ground Delay Program Enhancements (GDP-E). Work is currently underway to apply CDM technology and concepts in other areas including the distribution of NAS status information and the management of en-route traffic (Collaborative Routing). In this paper, we analyze the initial implementation of CDM. Our work is principally aimed at GDP-E since the other application areas are only now emerging. We show that CDM has had a positive impact on the quality of information and its distribution through increased accuracy of flight departures and the submission of more timely flight cancellation notices. The impact CDM has had on GDP planning and overall airline decision making is assessed. We also discuss the status of the Collaborative Routing effort and the issues involved in measuring its effectiveness.

86 citations


Journal ArticleDOI
Abstract: This paper analyzes criteria of fair division of a set of indivisible items among people whose revealed preferences are limited to rankings of the items and for whom no side payments are allowed. The criteria include refinements of Pareto optimality and envy-freeness as well as dominance-freeness, evenness of shares, and two criteria based on equally-spaced surrogate utilities, referred to as maxsum and equimax. Maxsum maximizes a measure of aggregate utility or welfare, whereas equimax lexicographically maximizes persons' utilities from smallest to largest. The paper analyzes conflicts among the criteria along with possibilities and pitfalls of achieving fair division in a variety of circumstances.

75 citations