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Collective voice of experts in multilateral negotiation
(Springer International Publishing, 2017)
Inspired from the ideas such as “algorithm portfolio”, “mixture of experts”, and “genetic algorithm”, this paper presents two novel negotiation strategies, which combine multiple negotiation experts to decide what to bid ...
Bottom-up approaches to achieve Pareto optimal agreements in group decision making
(Springer Nature, 2019-11)
In this article, we introduce a new paradigm to achieve Pareto optimality in group decision-making processes: bottom-up approaches to Pareto optimality. It is based on the idea that, while resolving a conflict in a group, ...
EXPECTATION: Personalized explainable artificial intelligence for decentralized agents with heterogeneous knowledge
(Springer, 2021)
Explainable AI (XAI) has emerged in recent years as a set of techniques and methodologies to interpret and explain machine learning (ML) predictors. To date, many initiatives have been proposed. Nevertheless, current ...
Actor-critic reinforcement learning for bidding in bilateral negotiation
(TÜBİTAK, 2022)
Designing an effective and intelligent bidding strategy is one of the most compelling research challenges in automated negotiation, where software agents negotiate with each other to find a mutual agreement when there is ...
Time series predictive models for opponent behavior modeling in bilateral negotiations
(Springer, 2023)
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 ...
A general-purpose protocol for multi-agent based explanations
(Springer, 2023)
Building on prior works on explanation negotiation protocols, this paper proposes a general-purpose protocol for multi-agent systems where recommender agents may need to provide explanations for their recommendations. The ...
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