Reyhan Aydoğan
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View article: Sharing Personal Data via Incentive-based Negotiation: Preference Modeling and Empirical Analysis
Sharing Personal Data via Incentive-based Negotiation: Preference Modeling and Empirical Analysis Open
In an age where data is a pivotal asset for businesses, the ethical acquisition and use of personal information has become increasingly more significant. Empowering data providers with greater autonomy over their personal data is more impo…
View article: UAV Marketplace Simulation Tool for BVLOS Operations
UAV Marketplace Simulation Tool for BVLOS Operations Open
We present a simulation tool for evaluating team formation in autonomous multi-UAV (Unmanned Aerial Vehicle) missions that operate Beyond Visual Line of Sight (BVLOS). The tool models UAV collaboration and mission execution in dynamic and …
View article: A Multitier Approach for Dynamic and Partially Observable Multiagent Path-Finding
A Multitier Approach for Dynamic and Partially Observable Multiagent Path-Finding Open
This paper introduces a novel Dynamic and Partially Observable Multiagent Path-Finding (DPO-MAPF) problem and presents a multitier solution approach accordingly. Unlike traditional MAPF problems with static obstacles, DPO-MAPF involves dyn…
View article: Computational persuasion technologies, explainability, and ethical-legal implications: A systematic literature review
Computational persuasion technologies, explainability, and ethical-legal implications: A systematic literature review Open
This paper conducts a systematic literature review (SLR) to evaluate the effectiveness of computational persuasion technology (CPT) in the eHealth domain. Over the past fifteen years, CPT has been used in various scenarios, from promoting …
View article: Two-stage Risk Control with Application to Ranked Retrieval
Two-stage Risk Control with Application to Ranked Retrieval Open
Practical machine learning systems often operate in multiple sequential stages, as seen in ranking and recommendation systems, which typically include a retrieval phase followed by a ranking phase. Effectively assessing prediction uncertai…
View article: InfVC: An Inference-Enhanced Local Search Algorithm for the Minimum Vertex Cover Problem in Massive Graphs
InfVC: An Inference-Enhanced Local Search Algorithm for the Minimum Vertex Cover Problem in Massive Graphs Open
The minimum vertex cover (MVC) problem is a classic NP-hard combinatorial optimization problem with extensive real-world applications. In this paper, we propose an efficient local search algorithm, InfVC, to solve the MVC in massive graphs…
View article: CALPAGAN: Calorimetry for Particles Using Generative Adversarial Networks
CALPAGAN: Calorimetry for Particles Using Generative Adversarial Networks Open
In this study, a novel approach is demonstrated for converting calorimeter images from fast simulations to those akin to comprehensive full simulations, utilizing conditional Generative Adversarial Networks (GANs). The concept of Pix2pix i…
View article: Scalable Primal Heuristics Using Graph Neural Networks for Combinatorial Optimization
Scalable Primal Heuristics Using Graph Neural Networks for Combinatorial Optimization Open
By examining the patterns of solutions obtained for various instances, one can gain insights into the structure and behavior of combinatorial optimization (CO) problems and develop efficient algorithms for solving them. Machine learning te…
View article: Decentralized multi-agent path finding framework and strategies based on automated negotiation
Decentralized multi-agent path finding framework and strategies based on automated negotiation Open
This paper introduces a negotiation framework to solve the Multi-Agent Path Finding (MAPF) Problem for self-interested agents in a decentralized fashion. The framework aims to achieve a good trade-off between the privacy of the agents and …
View article: Explainable Active Learning for Preference Elicitation
Explainable Active Learning for Preference Elicitation Open
Gaining insights into the preferences of new users and subsequently personaliz-ing recommendations necessitate managing user interactions intelligently, namely, posing pertinent questions to elicit valuable information effectively. In this…
View article: Towards interactive explanation-based nutrition virtual coaching systems
Towards interactive explanation-based nutrition virtual coaching systems Open
The awareness about healthy lifestyles is increasing, opening to personalized intelligent health coaching applications. A demand for more than mere suggestions and mechanistic interactions has driven attention to nutrition virtual coaching…
View article: CALPAGAN: Calorimetry for Particles using GANs
CALPAGAN: Calorimetry for Particles using GANs Open
In this study, a novel approach is demonstrated for converting calorimeter images from fast simulations to those akin to comprehensive full simulations, utilizing conditional Generative Adversarial Networks (GANs). The concept of pix2pix i…
View article: Conflict-based negotiation strategy for human-agent negotiation
Conflict-based negotiation strategy for human-agent negotiation Open
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 attitud…
View article: Effects of Agent's Embodiment in Human-Agent Negotiations
Effects of Agent's Embodiment in Human-Agent Negotiations Open
Human-agent negotiation has recently attracted researchers’ attention due to its complex nature and potential usage in daily life scenarios. While designing intelligent negotiating agents, they mainly focus on the interaction protocol (i.e…
View article: Explainable Active Learning for Preference Elicitation
Explainable Active Learning for Preference Elicitation Open
Gaining insights into the preferences of new users and subsequently personalizing recommendations necessitate managing user interactions intelligently, namely, posing pertinent questions to elicit valuable information effectively. In this …
View article: Explainable Active Learning for Preference Elicitation
Explainable Active Learning for Preference Elicitation Open
Gaining insights into the preferences of new users and subsequently personalizing recommendations necessitate managing user interactions intelligently, namely, posing pertinent questions to elicit valuable information effectively. In this …
View article: Feature extraction for enhancing data-driven urban building energy models
Feature extraction for enhancing data-driven urban building energy models Open
Building energy demand assessment plays a crucial role in designing energy-efficient building stocks. However, most studies adopting a data-driven approach feel the deficiency of datasets with building-specific information in building ener…
View article: Towards Interactive Explanation-based Nutrition Virtual Coaching Systems
Towards Interactive Explanation-based Nutrition Virtual Coaching Systems Open
The awareness about healthy lifestyles is increasing, opening to personalized intelligent health coaching applications. A demand for more than mere suggestions and mechanistic interactions has driven attention to nutrition virtual coaching…
View article: Decentralized Multi-Agent Path Finding Framework and Strategies Based on Automated Negotiation
Decentralized Multi-Agent Path Finding Framework and Strategies Based on Automated Negotiation Open
This paper introduces a negotiation framework to solve Multi-Agent Path Finding (MAPF) Problem for self-interested agents in a decentralized fashion. The framework aims to achieve a good trade-off between the privacy of the agents and the …
View article: The Effect of Appearance of Virtual Agents in Human-Agent Negotiation
The Effect of Appearance of Virtual Agents in Human-Agent Negotiation Open
Artificial Intelligence (AI) changed our world in various ways. People start to interact with a variety of intelligent systems frequently. As the interaction between human and AI systems increases day by day, the factors influencing their …
View article: Machine Learning to Predict Junction Temperature Based on Optical Characteristics in Solid-State Lighting Devices: A Test on WLEDs
Machine Learning to Predict Junction Temperature Based on Optical Characteristics in Solid-State Lighting Devices: A Test on WLEDs Open
While junction temperature control is an indispensable part of having reliable solid-state lighting, there is no direct method to measure its quantity. Among various methods, temperature-sensitive optical parameter-based junction temperatu…
View article: Actor-critic reinforcement learning for bidding in bilateral negotiation
Actor-critic reinforcement learning for bidding in bilateral negotiation Open
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 a conflict of inte…
View article: Bargaining Chips: Coordinating One-to-Many Concurrent Composite Negotiations
Bargaining Chips: Coordinating One-to-Many Concurrent Composite Negotiations Open
This study presents Bargaining Chips: a framework for one-to-many concurrent composite negotiations, where multiple deals can be reached and combined. Our framework is designed to mirror the salient aspects of real-life procurement and tra…
View article: Multi-objective evolutionary product bundling
Multi-objective evolutionary product bundling Open
[EN] Product bundling is a strategy conducted by marketing decisionmakers\nto combine items or services for targeted sales in today¿s\ncompetitive business environment. Targeted sales can be in various\nforms, like increasing the likelihoo…
View article: Can Social Agents Efficiently Perform in Automated Negotiation?
Can Social Agents Efficiently Perform in Automated Negotiation? Open
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 …