Searched for: subject%3A%22Automated%255C+negotiation%22
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Keskin, Mehmet Onur (author), Buzcu, Berk (author), Aydoğan, Reyhan (author)
Day by day, human-agent negotiation becomes more and more vital to reach a socially beneficial agreement when stakeholders need to make a joint decision together. Developing agents who understand not only human preferences but also attitudes is a significant prerequisite for this kind of interaction. Studies on opponent modeling are...
journal article 2023
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Yildirim, Ahmet Burak (author), Sunman, Nezih (author), Aydoğan, Reyhan (author)
The International Automated Negotiating Agent Competition introduces a new challenge each year to facilitate the research on agent-based negotiation and provide a test benchmark. ANAC 2020 addressed the problem of designing effective agents that do not know their users’ complete preferences in addition to their opponent’s negotiation strategy...
conference paper 2023
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Tejedor-Romero, Marino (author), Murukannaiah, P.K. (author), Gimenez-Guzman, Jose Manuel (author), Marsa-Maestre, Ivan (author), Jonker, C.M. (author)
Channel allocation in dense, decentralized Wi-Fi networks is a challenging due to the highly nonlinear solution space and the difficulty to estimate the opponent’s utility model. So far, only centralized or mediated approaches have succeeded in applying negotiation to this setting. We propose the first two fully-distributed negotiation...
conference paper 2023
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Yesevi, Gevher (author), Keskin, M.O. (author), Doğru, Anıl (author), Aydoğan, Reyhan (author)
In agent-based negotiations, it is crucial to understand the opponent’s behavior and predict its bidding pattern to act strategically. Foreseeing the utility of the opponent’s coming offer provides valuable insight to the agent so that it can decide its next move wisely. Accordingly, this paper addresses predicting the opponent’s coming...
conference paper 2023
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Tejedor Romero, M. (author), Murukannaiah, P.K. (author), Gimenez-Guzman, Jose Manuel (author), Marsa Maestre, I. (author), Jonker, C.M. (author)
Channel allocation in dense Wi-Fi networks is a complex problem due to its nonlinear and exponentially sized solution space. Negotiating over this domain is a challenge, since it is difficult to estimate opponent’s utility. Based on our previous work in mediated techniques, we propose the first two fully-distributed multi-agent negotiations...
conference paper 2023
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Xia, Lichen (author)
Automated negotiation is a key form of interaction in systems composed of multiple autonomous agents with different preferences. Such interactions aim to reach agreements through an iterative process of making offers. With the growth of Peer-to-Peer (P2P) energy markets due to the development and deployment of a variety of small-scale...
master thesis 2022
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Zhang, Peter (author)
Peer-to-peer trading and energy communities have garnered much attention over the last few years due to the wider spread of distributed energy resources. Much research has been performed on the mechanisms and methodologies behind their implementation and realisation. However, the efficiency and micro-structure of trading in such markets raise...
master thesis 2022
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Gaghi, Radu (author)
This paper introduces a strategy for learning opponent parameters in automated negotiation and using them for future negotiation sessions. The goal is to maximize the agent’s utility while being consistent in its performance over various negotiation scenarios. While a number of reinforcement learning approaches in the field have used Q-learning,...
bachelor thesis 2022
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Agrawal, Arpit (author)
With the prospects of decentralized multi-agent systems becoming more prevalent in daily life, automated negotiation agents have made their place in these collaborative settings. They are an approach to promote communication between the agents in reaching solutions that are better for all involved.<br/><br/>Recent literature has shown great...
bachelor thesis 2022
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Pocola, Octav (author)
Automated negotiation agents can highly benefit from learning their opponent’s preferences. Multiple algorithms have been developed with the two main categories being: heuristic techniques and machine learning techniques. Historically, heuristic techniques have dominated the field, but with the recent development in the field of machine learning...
bachelor thesis 2022
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Rubio Bizcaino, Andrzej (author)
This paper aims to define the broad concept of fairness and investigate how it can be measured, especially considering fairness in automated negotiations. The report relies on the work on fairness issues that have been derived from the research of C. Albin [1]. Firstly, the paper elaborates on different fairness metrics from the literature...
bachelor thesis 2022
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Blagoev, Nikolay (author)
As automated negotiating agents become more and more part of our daily life, additional care needs to be taken that the agents can negotiate fairly. Humans each have their own intrinsic view on fairness, which affects the negotiation processes and the degree to which the outcome is viewed as satisfactory. However, most current agents are built...
bachelor thesis 2022
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Ouwerkerk, Nick (author)
In this paper, the unintended consequences, also named edge cases in this paper, of integrating fairness into the automated negotiation process are researched. By finding these unintended consequences, we can deal with them accordingly or avoid them, as to not cause any problems with our fairness metric that might make our negotiation process...
bachelor thesis 2022
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Cochavi, Zohar (author)
The field of automated negotiation promises to improve negotiations, thus, a fair outcome and process should also be considered when building these systems. However, issues exist with computational approaches to fairness with which the field of computer science is mainly concerned. To this end, we propose a new approach to fairness based on that...
bachelor thesis 2022
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Koca, Thimjo (author), Baarslag, Tim (author), Jonker, C.M. (author)
This work presents BIDS (Bidding using Diversied Search), an algorithm that can be used by negotiating agents to search very large outcome spaces. BIDS provides a balance between being rapid, accurate, diverse, and scalable search, allowing agents to search spaces with as many as 10250 possible outcomes on very run-of-the-mill hardware. We<br/...
conference paper 2022
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Aydoğan, Reyhan (author), Baarslag, T. (author), Gerding, Enrico (author)
Conflict resolution is essential to obtain cooperation in many scenarios such as politics and business, as well as our day to day life. The importance of conflict resolution has driven research in many fields like anthropology, social science, psychology, mathematics, biology and, more recently, in artificial intelligence. Computer science...
contribution to periodical 2021
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Sanchez-Anguix, Victor (author), Tunalı, Okan (author), Aydoğan, Reyhan (author), Julian, Vicente (author)
In the last few years, we witnessed a growing body of literature about automated negotiation. Mainly, negotiating agents are either purely self-driven by maximizing their utility function or by assuming a cooperative stance by all parties involved in the negotiation. We argue that, while optimizing one’s utility function is essential, agents...
journal article 2021
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de Winkel, Eva (author)
Tighter profit margins and rising aircraft complexity are currently driving the need for aircraft maintenance organizations to increase efficiency. Many organizations believe that digitization is key for improving operational performance. Digitization of the task allocation process at a large aircraft maintenance organization did unexpectedly...
master thesis 2020
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Renting, B.M. (author), Hoos, Holger H. (author), Jonker, C.M. (author)
Bidding and acceptance strategies have a substantial impact on the outcome of negotiations in scenarios with linear additive and nonlinear utility functions. Over the years, it has become clear that there is no single best strategy for all negotiation settings, yet many fixed strategies are still being developed. We envision a shift in the...
conference paper 2020
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Renting, Bram (author)
Negotiation is the art of resolving conflicts of interests by finding outcomes that all parties agree with. Humans negotiate often, as there are many conflicts of interest in everyday life when working with other humans. Computer scientists have build computer agents that are capable of negotiating with each other in an attempt to outperform or...
master thesis 2019
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