259 research outputs found
Collaborative Decision-Making and the k-Strong Price of Anarchy in Common Interest Games
The control of large-scale, multi-agent systems often entails distributing
decision-making across the system components. However, with advances in
communication and computation technologies, we can consider new collaborative
decision-making paradigms that exist somewhere between centralized and
distributed control. In this work, we seek to understand the benefits and costs
of increased collaborative communication in multi-agent systems. We
specifically study this in the context of common interest games in which groups
of up to k agents can coordinate their actions in maximizing the common
objective function. The equilibria that emerge in these systems are the
k-strong Nash equilibria of the common interest game; studying the properties
of these states can provide relevant insights into the efficacy of inter-agent
collaboration. Our contributions come threefold: 1) provide bounds on how well
k-strong Nash equilibria approximate the optimal system welfare, formalized by
the k-strong price of anarchy, 2) study the run-time and transient performance
of collaborative agent-based dynamics, and 3) consider the task of redesigning
objectives for groups of agents which improve system performance. We study
these three facets generally as well as in the context of resource allocation
problems, in which we provide tractable linear programs that give tight bounds
on the k-strong price of anarchy.Comment: arXiv admin note: text overlap with arXiv:2308.0804
Maximizing Social Welfare in Score-Based Social Distance Games
Social distance games have been extensively studied as a coalition formation
model where the utilities of agents in each coalition were captured using a
utility function u that took into account distances in a given social network.
In this paper, we consider a non-normalized score-based definition of social
distance games where the utility function u_v depends on a generic scoring
vector v, which may be customized to match the specifics of each individual
application scenario.
As our main technical contribution, we establish the tractability of
computing a welfare-maximizing partitioning of the agents into coalitions on
tree-like networks, for every score-based function u_v. We provide more
efficient algorithms when dealing with specific choices of u_v or simpler
networks, and also extend all of these results to computing coalitions that are
Nash stable or individually rational. We view these results as a further strong
indication of the usefulness of the proposed score-based utility function: even
on very simple networks, the problem of computing a welfare-maximizing
partitioning into coalitions remains open for the originally considered
canonical function u.Comment: In Proceedings TARK 2023, arXiv:2307.0400
Collaborative Coalitions in Multi-Agent Systems: Quantifying the Strong Price of Anarchy for Resource Allocation Games
The emergence of new communication technologies allows us to expand our
understanding of distributed control and consider collaborative decision-making
paradigms. With collaborative algorithms, certain local decision-making
entities (or agents) are enabled to communicate and collaborate on their
actions with one another to attain better system behavior. By limiting the
amount of communication, these algorithms exist somewhere between centralized
and fully distributed approaches. To understand the possible benefits of this
inter-agent collaboration, we model a multi-agent system as a common-interest
game in which groups of agents can collaborate on their actions to jointly
increase the system welfare. We specifically consider -strong Nash
equilibria as the emergent behavior of these systems and address how well these
states approximate the system optimal, formalized by the -strong price of
anarchy ratio. Our main contributions are in generating tight bounds on the
-strong price of anarchy in finite resource allocation games as the solution
to a tractable linear program. By varying --the maximum size of a
collaborative coalition--we observe exactly how much performance is gained from
inter-agent collaboration. To investigate further opportunities for
improvement, we generate upper bounds on the maximum attainable -strong
price of anarchy when the agents' utility function can be designed
Maximizing Social Welfare in Score-Based Social Distance Games
Social distance games have been extensively studied as a coalition formation model where the utilities of agents in each coalition were captured using a utility function u that took into account distances in a given social network. In this paper, we consider a non-normalized score-based definition of social distance games where the utility function us̃ depends on a generic scoring vectors̃, which may be customized to match the specifics of each individual application scenario. As our main technical contribution, we establish the tractability of computing a welfare-maximizing partitioning of the agents into coalitions on tree-like networks, for every score-based function us̃. We provide more efficient algorithms when dealing with specific choices of us̃ or simpler networks, and also extend all of these results to computing coalitions that are Nash stable or individually rational. We view these results as a further strong indication of the usefulness of the proposed score-based utility function: even on very simple networks, the problem of computing a welfare-maximizing partitioning into coalitions remains open for the originally considered canonical function u
Solutions in multi-actor projects with collaboration and strategic incentives
This dissertation focuses on the mathematical analysis of projects involving decisions by multiple players. These players all have their own capabilities, requirements, and incentives, but their (monetary) outcome is dependent on the decisions of other players as well. Game theory is a mathematical tool to analyze the interactive decision-making process, generally paired with a method to ‘resolve’ the conflict situation. The way in which players interact in such a situation is commonly divided in two categories, distinguishing between cooperative and competitive (non-cooperative) behavior. This dissertation first studies two models within a cooperative framework, starting with the definition and analysis of a new influence measure for general, collaborative projects. The second model applies to situations where players cooperate on the construction of a new joint infrastructure, with a specific focus on cost allocation for CO2 transport infrastructure. Next, two-stage models are considered, in which a noncooperative first stage is followed by a cooperative second stage. Subsequently, social welfare loss in auctions with a corrupt auctioneer is studied. Finally, a new solution concept is presented that refines the notion of Nash equilibria for a general class of non-cooperative games
Nigeria-Biafra War and the Politics of Oblivion: Implications of Revealing the Hidden Narratives through Transformative Learning
Ignited by the secession of Biafra from Nigeria on May 30, 1967, the Nigeria-Biafra War (1967- 1970) with an estimated death toll of 3 million was followed by decades of silence and a ban of history education. However, the advent of democracy in 1999 catalyzed the return of repressed memories to public consciousness accompanied by renewed agitation for the secession of Biafra from Nigeria. The purpose of this study was to investigate whether a transformative learning of the Nigeria-Biafra War history will have a significant effect on conflict management styles of Nigerian citizens of Biafran origin regarding ongoing agitation for secession. Drawing on theories of knowledge, memory, forgetting, history, and transformative learning, and employing ex post facto research design, 320 participants were randomly selected from the Igbo ethnic group in the southeastern states of Nigeria to participate in transformative learning activities that focused on the Nigeria-Biafra War as well as complete both the Transformative Learning Survey (TLS) and Thomas-Kilmann Conflict Mode Instrument (TKI). Data collected were analyzed using descriptive analysis and inferential statistical tests. The results indicated that as transformative learning of the Nigeria-Biafra War history increased, collaboration also increased, while aggression decreased. From these findings, two effects emerged: transformative learning acted as a booster of collaboration and a reducer of aggression. This new understanding of transformative learning could help in conceptualizing a theory of transformative history education within the broader field of conflict resolution. The study therefore recommends that transformative learning of the Nigeria-Biafra War history should be implemented in Nigerian schools
Metadata Schema x-econ Repository
Since May 2017, the x-hub project partners OVGU Magdeburg, University of Vienna, and GESIS dispose of a new repository, called x-econ (https://x-econ.org). The service is dedicated to all experimental economics research projects to disseminate user-friendly archiving and provision of experimental economics research data. The repository x-econ contains all necessary core functionalities of a modern repository and is in a continuous optimization process aiming at functionality enhancement and improvement. x-econ is also one pillar of the multidisciplinary repository x-science (https://x-science.org). The present documentation, which is primarily based on the GESIS Technical Reports on datorium 2014|03 and da|ra 4.0, lists and explains the metadata elements, used to describe research information
Investigation of Game-Theoretic Mechanisms for the Valuation of Energy Resources
Electricity systems are facing the pressure to change in response to the effects of new technology, particularly the proliferation of renewable technologies (such as solar PV systems and wind generation) leading to the retirement of traditional generation technologies that provide stabilising inertia.
These changes create an imperative to consider potential future market structures to facilitate the participation of distributed energy resources (DERs; such as EVs and batteries) in grid operation.
However, this gives rise to general questions surrounding the ethics of market structures and how they could be fairly applied in future electricity systems. Particularly the most basic question "how should electricity be valued and traded" is fundamentally a moral question without any easy answer.
We give a survey of philosophical attitudes around such a question, before presenting a series of ways that these intuitions have been cast into mathematics, including: the Vickrey-Clarke-Groves mechanism, Locational Marginal Pricing, the Shapley Value, and Nash bargaining solution concepts.
We compared these different methods, and attempted a new synthesis that brought together the best features of each of them; called the 'Generalised Neyman and Kohlberg Value' or the GNK-value for short.
The GNK value was developed as a novel bargaining solution concept for many player non-cooperative transferable utility generalised games, and thus it was intrinsically flexible in its application to various aspects of powersystems.
We demonstrated the features of the GNK-value against the other mathematical solutions in the context of trading the immediate consumption/generation of power on small sized networks under linear-DC approximation, before extending the computation to larger networks.
The GNK value proved to be difficult to compute for large networks but was shown to be approximable for larger networks with a series of sampling techniques and a proxy method.
The GNK value was ethically compared to other mechanisms with the unfortunate discovery that it allowed for participants to be left worse-off for participating, violating the ethical notion of 'euvoluntary exchange' and 'individual rationality'; but was offered as an interesting innovation in the space of transferable utility generalised games notwithstanding.
For sampling the GNK value, there was a range of new and different techniques developed for stratified random sampling which iteratively minimise newly derived concentration inequalities on the error of the sampling.
These techniques were developed to assist in the computation of the GNK value to larger networks, and they were evaluated in the context of sampling synthetic data, and in computation of the Shapley Value of cooperative game theory.
These new sampling techniques were demonstrated to be comparable to the more orthodox Neyman sampling method despite not having access to stratum variances
Water Rites
What are the challenges surrounding water in Western Canada? What are our rights to water? Does water itself have rights? Water Rites: Reimagining Water in the West documents the many ways that water flows through our lives, connecting the humans, animals, and plants that all depend on this precious and endangered resource. Essays from scholars, activists, environmentalists, and human rights advocates illuminate the diverse issues surrounding water in Alberta, including the right to access clean drinking water, the competing demands of the resource development industry and Indigenous communities, and the dwindling supply of fresh water in the face of human-caused climate change. Statements from community organizations detail the challenges facing watersheds, and the actions being taken to mitigate these problems. With a special focus on Environmental and Indigenous issues, Water Rites explores how deeply water is tied to human life. These essays are complemented by full-colour portfolios of work by contemporary painters, photographers, and installation artists who explore our relation to water. Reproductions of historical paintings, engravings and film stills demonstrate how water has shaped our country’s cultural imaginary from its beginnings, proving that water is a vital resource for our lives and our imaginations
Dynamic Incentives for Optimal Control of Competitive Power Systems
This work presents a real-time dynamic pricing framework for future electricity markets. Deduced by first-principles analysis of physical, economic, and communication constraints within the power system, the proposed feedback control mechanism ensures both closed-loop system stability and economic efficiency at any given time. The resulting price signals are able to incentivize competitive market participants to eliminate spatio-temporal shortages in power supply quickly and purposively
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