Interdependent Multi-Issue Negotiation for Energy Exchange in Remote Communities

Alam, Muddasser; Rogers, Alex; Ramchurn, Sarvapali D.

doi:10.1609/aaai.v27i1.8614

Cited by 3 publications

(4 citation statements)

References 10 publications

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“…There is abundant research on interdependence extraction in negotiation [11,1]. For example, a method grouping highly interdependent issues by collecting meta-level information about the agenda in prior to the negotiation was developed and evaluated in [27].…”

Section: Interdependent Issuesmentioning

confidence: 99%

Divide-and-Conquer in Automated Negotiations Through Utility Decomposition

Hadfi

Ito

2023

IIAI Letters on Informatics and Interdisciplinary Research

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The success of a negotiation depends largely on the actors and the negotiation domain. It is common that negotiators rely on an agenda to simplify the process and reach better deals. This is particularly the case when the preferences of the negotiators are complex and when multiple issues are at stake. Using an agenda to explore and decompose the interdependence relationships between the issues is one way to address this problem. In this paper, we propose to address this challenge by applying the classical divide-andconquer approach to automated negotiations through means of utility decomposition and bottom-up agenda construction. The approach does not impose an agenda from the top level of the negotiations, but builds it bottom-up given the individual utility functions of the agents and the relationships between the issues. Our approach reduces the cost of exploring the utility spaces of the agents and the resulting bidding processes. We implement the approach in a novel protocol called the Decomposable Alternating Offers Proto-col (DAOP). The experimental results show that our divide-and-conquer algorithm makes a positive influence on the global performance of an automated negotiation system.

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Section: Interdependent Issuesmentioning

confidence: 99%

Divide-and-Conquer in Automated Negotiations Through Utility Decomposition

Hadfi

Ito

2023

IIAI Letters on Informatics and Interdisciplinary Research

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“…Game theory-based mechanisms can be leveraged where individual applications with greedy objectives can be considered players in a cooperative game and reducing the degree of conflict among the players can be considered as the benefit of a coalition. Some existing works have used such cooperative game methods for solving multi-microgrid [51] and virtual power plant management problems [52]. In a similar context, suitable deconfliction-related incentives could be designed to motivate applications to update their operational strategies to reduce conflict.…”

Section: ) Context and Cooperationmentioning

confidence: 99%

App Deconfliction: Orchestrating Distributed, Multi-Agent, Multi-Objective Operations for Power Systems

et al. 2023

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Advanced distribution systems need to integrate and orchestrate intelligent subsystems and grid-edge devices that are increasing both in number and sophistication while also serving multiple system-level objectives such as resilience, decarbonization, equity, and profitability. A modular platformbased approach to distribution system operations technology enables operators to deploy a tailored set of best-of-breed algorithms and applications. Combined with the parallel deployment and control of intelligent grid-edge and Internet-of-things devices, this creates a complex environment of distributedcontrol environment with applications that spans ownership boundaries. Conflicts can emerge between applications that want to control overlapping sets of device setpoints. We propose a formalized approach to resolving these conflicts that can be applied when integrating new algorithms or developing customized solutions. A Deconfliction Pipeline is inserted between the device-controlling applications and the device protocol converter, which transmits control setpoints from the operations platform to the devices. The Deconfliction Pipeline executes a process that sets up, solves, and acts on a formally defined deconfliction problem. The deconfliction problem can be solved using a combination of rules and heuristics, application engagement, and optimization. We demonstrate how a few of the most basic solution strategies can be used to orchestrate harmonious behavior between a pair of simple applications with conflicting greedy optimization objectives.

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“…max Any linear and continuous model can be replaced by KKT conditions by using Lagrangian functions. Therefore, the consumer utility function can be represented by KKT functions as in ( 13) and (14).…”

Section: Bi-level Optimizationmentioning

confidence: 99%

“…If there are heterogeneous sets of prosumers and consumers, the microgrid can enhance its revenues using P2P trading. The agent-based approach in [14] ensures the fair distribution of surpluses among agents. The resource distribution is modelled as a coalitional game and the contribution of agents is computed using the Shapley value.…”

Section: Introductionmentioning

confidence: 99%