Faruk Polat

E-mail
polatf@metu.edu.tr
Department
Department of Computer Engineering
Scopus Author ID
Web of Science Researcher ID
LIMP: Incremental Multi-agent Path Planning with LPA*
Yorganci, Mucahit Alkan; Semiz, Fatih; Polat, Faruk (2022-01-01)
The multi-agent pathfinding (MAPF) problem is defined as finding conflict-free paths for more than one agent. There exist optimal and suboptimal solvers for MAPF, and most of the solvers focus on the MAPF problem in static...
Multiagent Pickup and Delivery for Capacitated Agents
Çilden, Evren; Polat, Faruk (2022-01-01)
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.In Multi-Agent Pickup and Delivery (MAPD), multiple robots continuously receive tasks to pick up packages and deliver them to predefined dest...
Landmark based guidance for reinforcement learning agents under partial observability
Demir, Alper; Çilden, Erkin; Polat, Faruk (2022-01-01)
© 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.Under partial observability, a reinforcement learning agent needs to estimate its true state by solely using its obser...
Incremental multi-agent path finding
Semiz, Fatih; Polat, Faruk (Elsevier BV, 2021-03-01)
Existing multi-agent path finding (MAPF) algorithms are offline methods that aim at finding conflict-ree paths for more than one agent. In many real-life applications it is possible that a multi-agent plan cannot be fully ...
Compact Frequency Memory for Reinforcement Learning with Hidden States.
Polat, Faruk; Cilden, Erkin (2019-10-28)
Memory-based reinforcement learning approaches keep track of past experiences of the agent in environments with hidden states. This may require extensive use of memory that limits the practice of these methods in a real-li...
Effective feature reduction for link prediction in location-based social networks
Bayrak, Ahmet Engin; Polat, Faruk (SAGE Publications, 2019-10-01)
In this study, we investigated feature-based approaches for improving the link prediction performance for location-based social networks (LBSNs) and analysed their performances. We developed new features based on time, com...
Automatic landmark discovery for learning agents under partial observability
DEMİR, ALPER; Cilden, Erkin; Polat, Faruk (Cambridge University Press (CUP), 2019-08-02)
In the reinforcement learning context, a landmark is a compact information which uniquely couples a state, for problems with hidden states. Landmarks are shown to support finding good memoryless policies for Partially Obse...
GENERATING EFFECTIVE INITIATION SETS FOR SUBGOAL-DRIVEN OPTIONS
DEMİR, ALPER; Cilden, Erkin; Polat, Faruk (World Scientific Pub Co Pte Lt, 2019-03-01)
Options framework is one of the prominent models serving as a basis to improve learning speed by means of temporal abstractions. An option is mainly composed of three elements: initiation set, option's local policy and ter...
A context aware model for autonomous agent stochastic planning
Ekmekci, Ömer; Polat, Faruk (Elsevier BV, 2019-02-01)
Markov Decision Processes (MDPs) are not able to make use of domain information effectively due to their representational limitations. The lacking of elements which enable the models be aware of context, leads to unstructu...
Effective induction of gene regulatory networks using a novel recommendation method
Ozsoy, Makbule Gulcin; Polat, Faruk; Alhajj, Reda (2019-01-01)
In this paper, we introduce a method based on recommendation systems to predict the structure of Gene Regulatory Networks (GRNs) making use of data from multiple sources. Our method is based on collaborative filtering appr...
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