Searched for: subject%3A%22Opponent%255C%2BModelling%22
(1 - 10 of 10)
document
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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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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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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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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Trestioreanu, Ilinca (author)
Is there a way to incorporate fairness in the opponent modeling component of an automated agent? Since opponent modeling plays an important role in a negotiation strategy, it is reasonable to research how fairness can be integrated into this component, as it influences the outcome of the negotiation. A first step towards finding an answer to...
bachelor thesis 2022
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van der Toorn, Eric (author)
A recent advancement in Reinforcement Learning is the capability of modelling opponents. In this work, we are interested in going back to basics and testing this capability within the Iterated Prisoner's Dilemma, a simple method for modelling multi agent systems. Using the self modelling advantage actor critic model, we set up a single agent...
bachelor thesis 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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Baarslag, T. (author), Hendrikx, M.J.C. (author), Hindriks, K.V. (author), Jonker, C.M. (author)
A negotiation between agents is typically an incomplete information game, where the agents initially do not know their opponent’s preferences or strategy. This poses a challenge, as efficient and effective negotiation requires the bidding agent to take the other’s wishes and future behavior into account when deciding on a proposal. Therefore, in...
journal article 2015
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Baarslag, T. (author)
Negotiation is an important activity in human society, and is studied by various disciplines, ranging from economics and game theory, to electronic commerce, social psychology, and artificial intelligence. Traditionally, negotiation is a necessary, but also time-consuming and expensive activity. Therefore, in the last decades there has been a...
doctoral thesis 2014
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Hendrikx, M.J.C. (author)
Automated negotiation agents are agents that interact in an environment for the settlement of a mutual concern. An important factor influencing the performance of a negotiation agent is how it takes the opponent into account. The main challenge in this aspect, is that opponents typically hide private information to avoid exploitation. In such a...
master thesis 2012
Searched for: subject%3A%22Opponent%255C%2BModelling%22
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