Faruk Polat

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ABSTRACTION IN REINFORCEMENT LEARNING IN PARTIALLY OBSERVABLE ENVIRONMENTS A THESIS SUBMITTED TO THE GRADUATE SCHOOL OF NATURAL AND APPLIED SCIENCES OF MIDDLE EAST TECHNICAL UNIVERSITY ERKİN ÇİLDEN IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY

C. Özgen, Faruk Polat, 2014 .

Automated Large-Scale Control of Gene Regulatory Networks

Reda Alhajj, Mehmet Tan, Faruk Polat, 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

Cluster Stability Analysis using Subsampling

R. Alhajj, Faruk Polat, Osman Abul, 2003 .

Effective induction of gene regulatory networks using a novel recommendation method

Reda Alhajj, Faruk Polat, Makbule Gulcin Ozsoy, 2019, Int. J. Data Min. Bioinform..

Converting a Legacy Database to Object-Oriented Database

Reda Alhajj, Faruk Polat, R. Alhajj, 2005, Encyclopedia of Database Technologies and Applications.

A layered approach to learning coordination knowledge in multiagent environments

Faruk Polat, Güray Erus, G. Erus, 2007, Applied Intelligence.

Learning Sequences of Compatible Actions Among Agents

Faruk Polat, Osman Abul, Faruk Polat, 2002, Artificial Intelligence Review.

Multiagent reinforcement learning using function approximation

Reda Alhajj, Faruk Polat, Osman Abul, 2000, IEEE Trans. Syst. Man Cybern. Part C.

Coordination of intelligent agents in real‐time search

Faruk Polat, Armagan Cakir, Faruk Polat, 2002, Expert Syst. J. Knowl. Eng..

Compact Frequency Memory for Reinforcement Learning with Hidden States

Faruk Polat, Erkin Çilden, Hüseyin Aydin, 2019, PRIMA.

Using Transitional Bottlenecks to Improve Learning in Nearest Sequence Memory Algorithm

Faruk Polat, Erkin Çilden, Hüseyin Aydin, 2017, 2017 IEEE 29th International Conference on Tools with Artificial Intelligence (ICTAI).

Toward Generalization of Automated Temporal Abstraction to Partially Observable Reinforcement Learning

Faruk Polat, Erkin Çilden, Faruk Polat, 2015, IEEE Transactions on Cybernetics.

Employing Automatic Temporal Abstractions to Accelerate Utile Suffix Memory Algorithm

Faruk Polat, Erkin Çilden, Faruk Polat, 2014, MATES.

Generating Memoryless Policies Faster Using Automatic Temporal Abstractions for Reinforcement Learning with Hidden State

Faruk Polat, Erkin Çilden, Faruk Polat, 2013, 2013 IEEE 25th International Conference on Tools with Artificial Intelligence.

Landmark Based Reward Shaping in Reinforcement Learning with Hidden States

Faruk Polat, Alper Demir, Erkin Çilden, 2019, AAMAS.

Batch Mode TD($\lambda$ ) for Controlling Partially Observable Gene Regulatory Networks

Reda Alhajj, Faruk Polat, Utku Sirin, 2017, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

Subtree selection in kernels for graph classification

Reda Alhajj, Mehmet Tan, Faruk Polat, 2013, Int. J. Data Min. Bioinform..

LIMP: Incremental Multi-agent Path Planning with LPA

Faruk Polat, Mücahit Alkan Yorgancı, Fatih Semiz, 2022, ICAART.

Incremental multi-agent path finding

Faruk Polat, Fatih Semiz, Faruk Polat, 2021, Future Gener. Comput. Syst..

MOD* Lite: An Incremental Path Planning Algorithm Taking Care of Multiple Objectives

Faruk Polat, Tugcem Oral, Faruk Polat, 2016, IEEE Transactions on Cybernetics.

A Multi-objective Incremental Path Planning Algorithm for Mobile Agents

Faruk Polat, Tugcem Oral, Faruk Polat, 2012, 2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology.

An Evolutionary Approach for Detecting Communities in Social Networks

Tansel Özyer, Faruk Polat, Koray Ozturk, 2017, 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM).

Influence of Prior Knowledge in Constraint-Based Learning of Gene Regulatory Networks

Mohammed Al-Shalalfa, Reda Alhajj, Mehmet Tan, 2011, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

Large-scale approximate intervention strategies for Probabilistic Boolean Networks as models of gene regulation

Reda Alhajj, Mehmet Tan, Faruk Polat, 2008, 2008 8th IEEE International Conference on BioInformatics and BioEngineering.

Improving reinforcement learning by using sequence trees

Reda Alhajj, Faruk Polat, Sertan Girgin, 2010, Machine Learning.

Landmark based guidance for reinforcement learning agents under partial observability

Faruk Polat, Alper Demir, Erkin Çilden, 2022, International Journal of Machine Learning and Cybernetics.

Using chains of bottleneck transitions to decompose and solve reinforcement learning tasks with hidden states

Faruk Polat, Hüseyin Aydin, Erkin Çilden, 2022, Future Gener. Comput. Syst..

Automatic landmark discovery for learning agents under partial observability

Faruk Polat, Alper Demir, Erkin Çilden, 2019, The Knowledge Engineering Review.

Employing decomposable partially observable Markov decision processes to control gene regulatory networks

Reda Alhajj, Faruk Polat, Utku Erdogdu, 2017, Artif. Intell. Medicine.

A Concept Filtering Approach for Diverse Density to Discover Subgoals in Reinforcement Learning

Faruk Polat, Alper Demir, Erkin Çilden, 2017, 2017 IEEE 29th International Conference on Tools with Artificial Intelligence (ICTAI).

Abstraction in Model Based Partially Observable Reinforcement Learning Using Extended Sequence Trees

Faruk Polat, Erkin Çilden, Faruk Polat, 2012, 2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology.

Learning Intelligent Behavior in a Non-stationary and Partially Observable Environment

Faruk Polat, Selguk Senkul, Faruk Polat, 2002, Artificial Intelligence Review.

A Negotiation Platform for Cooperating Multi-agent Systems

Shashi Shekhar, Faruk Polat, H. A. Guvenir, 1993 .

Using Object-Oriented Materialized Views to Answer Selection-Based Complex Queries

Reda Alhajj, Faruk Polat, R. Alhajj, 1999, Inf. Sci..

Revealing miRNA Regulation and miRNA Target Prediction Using Constraint-Based Learning

Jon G. Rokne, Mohammed Al-Shalalfa, Reda Alhajj, 2012, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

Multilevel graph partitioning: an evolutionary approach

Halit Oguztüzün, F. Polat, S. Küçükpetek, 2005, J. Oper. Res. Soc..

Solving Area Coverage Problem with UAVs: A Vehicle Routing with Time Windows Variation pdf

Faruk Polat, Fatih Semiz, Faruk Polat, 2020, Robotics Auton. Syst..

RTTES: Real-time search in dynamic environments

Faruk Polat, Cagatay Undeger, Faruk Polat, 2007, Applied Intelligence.

Real time target evaluation search

Faruk Polat, Cagatay Undeger, Faruk Polat, 2006, AAMAS '06.

Employment of an evolutionary heuristic to solve the target allocation problem efficiently

Faruk Polat, Ahmet Engin Bayrak, Faruk Polat, 2013, Inf. Sci..

Limited-Damage A*: A path search algorithm that considers damage as a feasibility criterion

Faruk Polat, Serhat Bayili, Faruk Polat, 2011, Knowl. Based Syst..

Employing Batch Reinforcement Learning to Control Gene Regulation Without Explicitly Constructing Gene Regulatory Networks

Reda Alhajj, Faruk Polat, Utku Sirin, 2013, IJCAI.

Real-Time Edge Follow: A Real-Time Path Search Approach

Faruk Polat, Cagatay Undeger, Faruk Polat, 2007, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

Implementing Agent Communication for a Multi-agent Simulation Infrastructure on HLA

Faruk Polat, Erek Göktürk, Faruk Polat, 2003, ISCIS.

Making recommendations by integrating information from multiple social networks

Reda Alhajj, Faruk Polat, Makbule Gulcin Ozsoy, 2016, Applied Intelligence.

Trust based recommendation systems

Faruk Polat, Makbule Gulcin Ozsoy, Faruk Polat, 2013, 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2013).

Realizing drug repositioning by adapting a recommendation system to handle the process

R. Alhajj, Faruk Polat, Tansel Özyer, 2018, BMC Bioinformatics.

Positive Impact of State Similarity on Reinforcement Learning Performance

Reda Alhajj, Faruk Polat, Sertan Girgin, 2007, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

A Powerful Approach for Effective Finding of Significantly Differentially Expressed Genes

Reda Alhajj, Faruk Polat, Osman Abul, 2006, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

Feature selection for graph kernels

Reda Alhajj, Mehmet Tan, Faruk Polat, 2010, 2010 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

A multi-agent tuple-space based problem solving framework

Reda Alhajj, Faruk Polat, R. Alhajj, 1999, J. Syst. Softw..

Correction: Landmark based guidance for reinforcement learning agents under partial observability

Faruk Polat, Alper Demir, Erkin Çilden, 2022, International Journal of Machine Learning and Cybernetics.

Mining Individual Features to Enhance Link Prediction Efficiency in Location Based Social Networks

Faruk Polat, Ahmet Engin Bayrak, Faruk Polat, 2018, 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM).

Function approximation based multi-agent reinforcement learning

Reda Alhajj, Faruk Polat, Osman Abul, 2000, Proceedings 12th IEEE Internationals Conference on Tools with Artificial Intelligence. ICTAI 2000.

Employing multi-agents to identify touching of adjacent digits in handwritten Hindi numerals

Ashraf Elnagar, Reda Alhajj, Faruk Polat, 2000, Smc 2000 conference proceedings. 2000 ieee international conference on systems, man and cybernetics. 'cybernetics evolving to systems, humans, organizations, and their complex interactions' (cat. no.0.

Generating Effective Initiation Sets for Subgoal-Driven options

Faruk Polat, Alper Demir, Erkin Çilden, 2019, Adv. Complex Syst..

A context aware model for autonomous agent stochastic planning

Faruk Polat, Omer Ekmekci, Faruk Polat, 2019, Robotics Auton. Syst..

Local Roots: A Tree-Based Subgoal Discovery Method to Accelerate Reinforcement Learning

Faruk Polat, Alper Demir, Erkin Çilden, 2016, ECML/PKDD.

Memory efficient factored abstraction for reinforcement learning

Faruk Polat, Erkin Çilden, Coskun Sahin, 2015, 2015 IEEE 2nd International Conference on Cybernetics (CYBCONF).

Reda Alhajj, Faruk Polat, Sertan Girgin, 2007, IJCAI.

Effectiveness of Considering State Similarity for Reinforcement Learning

Reda Alhajj, Faruk Polat, Sertan Girgin, 2006, IDEAL.

Learning by Automatic Option Discovery from Conditionally Terminating Sequences

Reda Alhajj, Faruk Polat, Sertan Girgin, 2006, ECAI.

Option Discovery in Reinforcement Learning using Frequent Common Subsequences of Actions

Faruk Polat, Sertan Girgin, Sertan Girgin, 2005, International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and Internet Commerce (CIMCA-IAWTIC'06).

Effective gene expression data generation framework based on multi-model approach

Reda Alhajj, Mehmet Tan, Faruk Polat, 2016, Artif. Intell. Medicine.

Integrating machine learning techniques into robust data enrichment approach and its application to gene expression data

Reda Alhajj, Jon G. Rokne, Mehmet Tan, 2013, Int. J. Data Min. Bioinform..

Effective Enrichment of Gene Expression Data Sets

Reda Alhajj, Mehmet Tan, Faruk Polat, 2012, 2012 11th International Conference on Machine Learning and Applications.

Employing Machine Learning Techniques for Data Enrichment: Increasing the Number of Samples for Effective Gene Expression Data Analysis

Reda Alhajj, Jon G. Rokne, Mehmet Tan, 2011, 2011 IEEE International Conference on Bioinformatics and Biomedicine.

TempoXML: Nested bitemporal relationship modeling and conversion tool for fuzzy XML

Tansel Özyer, Reda Alhajj, Faruk Polat, 2012, Inf. Sci..

Combining multiple types of biological data in constraint-based learning of gene regulatory networks

Mohammed Al-Shalalfa, Reda Alhajj, Mehmet Tan, 2008, 2008 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology.

Modeling individuals and making recommendations using multiple social networks

Reda Alhajj, Faruk Polat, Makbule Gulcin Ozsoy, 2015, 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM).

Scalable approach for effective control of gene regulatory networks

Reda Alhajj, Mehmet Tan, Faruk Polat, 2010, Artif. Intell. Medicine.

Time preference aware dynamic recommendation enhanced with location, social network and temporal information

Reda Alhajj, Faruk Polat, Makbule Gulcin Ozsoy, 2016, 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM).

Multi-objective optimization based location and social network aware recommendation

Reda Alhajj, Faruk Polat, Makbule Gulcin Ozsoy, 2014, 10th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing.

Distributed conflict resolution among cooperating expert systems

Shashi Shekhar, Faruk Polat, H. Altay Güvenir, 1993 .

Realizing drug repositioning by adapting a recommendation system to handle the process

Tansel Özyer, Reda Alhajj, Faruk Polat, 2018, BMC Bioinformatics.

Semantic information-based alternative plan generation for multiple query optimization

Reda Alhajj, Ahmet Cosar, Faruk Polat, 2001, Inf. Sci..

A Conflict Resolution-Based Decentralized Multi-Agent Problem Solving Model

Faruk Polat, H. Altay Güvenir, H. Altay Güvenir, 1992, MAAMAW.

Finding differentially expressed genes for pattern generation

Reda Alhajj, Ken Barker, Faruk Polat, 2005, Bioinform..

Derivation of Transcriptional Regulatory Relationships by Partial Least Squares Regression

Reda Alhajj, Mehmet Tan, Faruk Polat, 2009, 2009 IEEE International Conference on Bioinformatics and Biomedicine.