Browsing by Author "Eran, Cihan"

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    A decentralized token-based negotiation approach for multi-agent path finding
    (Springer, 2021) Eran, Cihan; Keskin, Mehmet Onur; Cantürk, Furkan; Aydoğan, Reyhan; Computer Science; AYDOĞAN, Reyhan; Eran, Cihan; Keskin, Mehmet Onur; Cantürk, Furkan
    This paper introduces a negotiation approach to solve the Multi-Agent Path Finding problem. The approach aims to achieve a good trade-off between the privacy of the agents and the effectiveness of solutions. Accordingly, a token-based bilateral negotiation protocol and a compatible negotiation strategy are presented. The proposed approach is evaluated in a variety of scenarios by comparing it with state-of-the-art centralized approaches such as Conflict Based Search and its variant. The experimental results showed that the proposed approach can find conflict-free path solutions with a higher success rate, especially when the search space is large and high-density compared to centralized approaches while the gap between path cost differences is reasonably low. The proposed approach enables agents to have their autonomy; thus, it is convenient for MAPF problems involving self-interested agents.
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    MedSpecSearch: Medical specialty search
    (Springer Nature, 2019) Şahin, Mehmet Uluç; Balatkan, Eren; Eran, Cihan; Zeydan, E.; Yeniterzi, Reyyan; Computer Science; YENİTERZİ, Reyyan; Şahin, Mehmet Uluç; Balatkan, Eren; Eran, Cihan
    MedSpecSearch (www.medspecsearch.com) is a search engine for helping users to find the relevant medical specialty for a doctor visit based on users’ description of symptoms. This system is useful for users who are not sure of which medical specialty they should consult to. Furthermore, the API of the search engine can be used as part of the online doctor appointment and medical consultation sites to route the patient or question to the right medical specialty. The system returns the top three relevant specialties when the estimated confidence score is high. Otherwise, it asks users to input more data.
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    Master ThesisPublicationMetadata only
    Negotiation-based decentralized conflict resolution in multi-agent path finding
    Eran, Cihan; Aydoğan, Reyhan; Aydoğan, Reyhan; Kıraç, Mustafa Furkan; Korçak, Ö.; Department of Computer Science; Eran, Cihan
    This thesis addresses the problem of Multi-Agent Path Finding problem where multiple agents aim to reach their destination in a grid world without any colli sion. It aims to provide a solution achieving good trade-off between the privacy of the agents and the effectiveness of solutions. Accordingly, a token-based bilateral negotiation approach is presented to solve this problem in a distributed way. The proposed approach is evaluated empirically in various scenarios by comparing it with state-of-the-art centralized approaches such as Conflict Based Search and its variants. The experimental results showed that the proposed approach can find conflict-free path solutions albeit suboptimally, especially when the search space is large and high-density, whereas centralized approaches struggle to find optimal solutions. Despite being outperformed by suboptimal centralized solvers, the pro posed decentralized approach can achieve considerable results with naive agents by sharing minimal information about themselves. The proposed approach also enables agents to have their autonomy; thus, the proposed approach is convenient for MAPF problems involving self-interested agents.