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2020 – today
- 2024
[j7]Saim Sunel
, Erkin Çilden, Faruk Polat:
Faster MIL-based Subgoal Identification for Reinforcement Learning by Tuning Fewer Hyperparameters. ACM Trans. Auton. Adapt. Syst. 19(2): 10 (2024)- 2023
- [j6]Alper Demir, Erkin Çilden, Faruk Polat:
Landmark based guidance for reinforcement learning agents under partial observability. Int. J. Mach. Learn. Cybern. 14(4): 1543-1563 (2023) - [j5]Alper Demir, Erkin Çilden, Faruk Polat:
Correction: Landmark based guidance for reinforcement learning agents under partial observability. Int. J. Mach. Learn. Cybern. 14(4): 1565 (2023) - 2022
- [j4]Hüseyin Aydin, Erkin Çilden, Faruk Polat:
Using chains of bottleneck transitions to decompose and solve reinforcement learning tasks with hidden states. Future Gener. Comput. Syst. 133: 153-168 (2022)
2010 – 2019
- 2019
- [j3]Alper Demir, Erkin Çilden, Faruk Polat:
Generating Effective Initiation Sets for Subgoal-Driven options. Adv. Complex Syst. 22(2): 1950001:1-1950001:32 (2019) - [j2]Alper Demir, Erkin Çilden, Faruk Polat:
Automatic landmark discovery for learning agents under partial observability. Knowl. Eng. Rev. 34: e11 (2019) - [c14]Alper Demir, Erkin Çilden, Faruk Polat:
Landmark Based Reward Shaping in Reinforcement Learning with Hidden States. AAMAS 2019: 1922-1924 - [c13]Hüseyin Aydin, Erkin Çilden, Faruk Polat:
Compact Frequency Memory for Reinforcement Learning with Hidden States. PRIMA 2019: 425-433 - [c12]Muhammed Cagri Kaya, Alper Karamanlioglu, I. Çaglar Çetintas, Erkin Çilden, M. Haluk Canberi, Halit Oguztüzün:
A configurable gateway for DDS-HLA interoperability. SummerSim 2019: 36:1-36:11 - [c11]Gökçe Özkan, Erkin Çilden, Emre Gültekin, Ahmet Sezer, M. Haluk Canberi:
A reference architecture for military simulations with experimentation and analysis features. SummerSim 2019: 64:1-64:6 - 2018
- [c10]Erkin Çilden, Emre Gultekin, Dogan Poyraz, M. Haluk Canberi:
A Generic Distributed Architecture to Integrate Simulated Participants with Modular Avionics. DS-RT 2018: 222-223 - [c9]Erhan Ceran, Erkin Çilden, Emre Gultekin, M. Haluk Canberi:
Network packet loss sensitivity analysis for sympes codec. SIU 2018: 1-4 - 2017
- [c8]Alper Demir, Erkin Çilden, Faruk Polat:
A Concept Filtering Approach for Diverse Density to Discover Subgoals in Reinforcement Learning. ICTAI 2017: 1-5 - [c7]Hüseyin Aydin, Erkin Çilden, Faruk Polat:
Using Transitional Bottlenecks to Improve Learning in Nearest Sequence Memory Algorithm. ICTAI 2017: 147-152 - 2016
- [c6]Alper Demir, Erkin Çilden, Faruk Polat:
A History Tree Heuristic to Generate Better Initiation Sets for Options in Reinforcement Learning. ECAI 2016: 1644-1645 - [c5]Alper Demir, Erkin Çilden, Faruk Polat:
Local Roots: A Tree-Based Subgoal Discovery Method to Accelerate Reinforcement Learning. ECML/PKDD (2) 2016: 361-376 - 2015
- [j1]Erkin Çilden, Faruk Polat:
Toward Generalization of Automated Temporal Abstraction to Partially Observable Reinforcement Learning. IEEE Trans. Cybern. 45(8): 1414-1425 (2015) - [c4]Coskun Sahin, Erkin Çilden, Faruk Polat:
Memory efficient factored abstraction for reinforcement learning. CYBCONF 2015: 18-23 - 2014
- [b1]Erkin Çilden:
Abstraction in reinforcement learning in partially observable environments ; Kısmi gözlemlenebilir ortamlar için pekiştirmeli öğrenmede soyutlama. Middle East Technical University, Çankaya, Ankara, Turkey, 2014 - [c3]Erkin Çilden, Faruk Polat:
Employing Automatic Temporal Abstractions to Accelerate Utile Suffix Memory Algorithm. MATES 2014: 156-169 - 2013
- [c2]Erkin Çilden, Faruk Polat:
Generating Memoryless Policies Faster Using Automatic Temporal Abstractions for Reinforcement Learning with Hidden State. ICTAI 2013: 719-726 - 2012
- [c1]Erkin Çilden, Faruk Polat:
Abstraction in Model Based Partially Observable Reinforcement Learning Using Extended Sequence Trees. IAT 2012: 348-355
Coauthor Index
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last updated on 2024-08-05 21:12 CEST by the dblp team
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