Browsing by Author "Aydoğan, Reyhan"
Now showing items 1-20 of 45
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An actor-critic reinforcement learning approach for bilateral negotiation
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 ... -
Adapting bilateral networks to monocular depth estimation for real-time inference
Monocular Depth Estimation (MDE) is a fundamental computer vision application area for many industry-related advances. Due to its deployment needs, the inference time of the depth estimation algorithm also plays a crucial ... -
Agent based negotiation for incentive driven privacy preserving information sharing
Razeghi, Yousef (2019-08-20)While customizing their services, companies usually use their users’ data. According to the new regularization, it is required to get the permission of their users to be able to store and share their users’ private data. ... -
Algorithm selection and combining multiple learners for residential energy prediction
Güngör, Onat; Akşanlı, B.; Aydoğan, Reyhan (Elsevier, 2019-10)Balancing supply and demand management in energy grids requires knowing energy consumption in advance. Therefore, forecasting residential energy consumption accurately plays a key role for future energy systems. For this ... -
Alternating offers protocols for multilateral negotiation
Aydoğan, Reyhan; Festen, D.; Hindriks, K. V.; Jonker, C. M. (Springer International Publishing, 2017)This paper presents a general framework for multilateral turn-taking protocols and two fully specified protocols namely Stacked Alternating Offers Protocol (SAOP) and Alternating Multiple Offers Protocol (AMOP). In SAOP, ... -
ANAC 2018: Repeated multilateral negotiation league
Aydoğan, Reyhan; Fujita, K.; Baarslag, T.; Jonker, C. M.; Ito, T. (Springer, 2020)This is an extension from a selected paper from JSAI2019. There are a number of research challenges in the field of Automated Negotiation. The Ninth International Automated Negotiating Agent Competition encourages participants ... -
Artificial intelligence tools for academic management: assigning students to academic supervisors
Sanchez-Anguix, V.; Chalumuri, R.; Alberola, J. M.; Aydoğan, Reyhan (International Academy of Technology, Education and Development (IATED), 2020)In the last few years, there has been a broad range of research focusing on how learning should take place both in the classroom and outside the classroom. Even though academic dissertations are a vital step in the academic ... -
Associative and frequentist opponent modeling approaches in automated bilateral negotiations
This thesis mainly focuses on the problem of learning opponent's preferences during the negotiation in bilateral automated negotiation in which agents negotiate with each other to reach an agreement. Accordingly, it addresses ... -
Automated negotiating agents competition (ANAC)
Jonker, C. M.; Aydoğan, Reyhan; Baarslag, T.; Fujita, K.; Ito, T.; Hindiks, K. (AAAI press, 2017)The annual International Automated Negotiating Agents Competition (ANAC) is used by the automated negotiation research community to benchmark and evaluate its work and to challenge itself. The benchmark problems and ... -
Black-box test case selection by relating code changes with previously fixed defects
Software continuously changes to address new requirements and to fix defects. Regression testing is performed to ensure that the applied changes do not adversely affect existing functionality. The increasing number of test ... -
Bottom-up approaches to achieve Pareto optimal agreements in group decision making
Sanchez-Anguix, V.; Aydoğan, Reyhan; Baarslag, T.; Jonker, C. (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, ... -
Campaign participation prediction with deep learning
Ayvaz, Demet; Aydoğan, Reyhan; Akçura, Munir Tolga; Şensoy, Murat (Elsevier, 2021-08)Increasingly, on-demand nature of customer interactions put pressure on companies to build real-time campaign management systems. Instead of having managers to decide on the campaign rules, such as, when, how and whom to ... -
The challenge of negotiation in the game of diplomacy
de Jonge, D.; Baarslag, T.; Aydoğan, Reyhan; Jonker, C.; Fujita, K.; Ito, T. (Springer Nature, 2019)The game of Diplomacy has been used as a test case for complex automated negotiations for a long time, but to date very few successful negotiation algorithms have been implemented for this game. We have therefore decided ... -
Challenges and main results of the automated negotiating agents competition (ANAC) 2019
Aydoğan, Reyhan; Baarslag, T.; Fujita, K.; Mell, J.; Gratch, J.; de Jonge, D.; Mohammad, Y.; Nakadai, S.; Morinaga, S.; Osawa, H.; Aranha, C.; Jonker, C. M. (Springer, 2020)The Automated Negotiating Agents Competition (ANAC) is a yearly-organized international contest in which participants from all over the world develop intelligent negotiating agents for a variety of negotiation problems. ... -
Clothing image retrieval with triplet capsule networks
Kınlı, Osman Furkan (2019-08-19)Clothing image retrieval has become more important after some major developments in Computer Science and the emergence of e-commerce. Recent studies generally attack this problem by using Convolutional Neural Networks ... -
Collective voice of experts in multilateral negotiation
Güneş, Taha Doğan; Arditi, Emir; Aydoğan, Reyhan (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 ... -
Conflict resolution in decision making - Second international workshop, COREDEMA 2016, The Hague, The Netherlands, August 29-30, 2016, Revised Selected Papers
Aydoğan, Reyhan (Springer International Publishing, 2017) -
Deep reinforcement learning for acceptance strategy in bilateral negotiations
Razeghi, Yousef; Yavuz, Ozan; Aydoğan, Reyhan (TÜBİTAK, 2020)This paper introduces an acceptance strategy based on reinforcement learning for automated bilateral negotiation, where negotiating agents bargain on multiple issues in a variety of negotiation scenarios. Several acceptance ... -
Effect of embodiment in human-agent negotiations
With the current advancement in artificial intelligence, intelligent systems interacting with humans are becoming more prevalent in our lives. One of the challenges is building socially intelligent agents who can effectively ... -
Explorations on inverse reinforcement learning for the analysis of motor control and cognitive decision making mechanisms of the brain
Reinforcement Learning is a framework for generating optimal policies given a task and a reward/punishment structure. Likewise, Inverse Reinforcement Learning, as the name suggests, is used for recovering the reasoning ...
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