4 citations · 7 across the 6 of their papers we have counts for
8 papers
SpecMAGIC: Specification-Guided Multi-Task Generalization in Multi-Agent Reinforcement Learning
Zijian Guo, İlker Işık, H. M. Sabbir Ahmad +1
Multi-task generalization is an important yet underexplored problem in multi-agent reinforcement learning (MARL). Many real-world applications require multi-agent systems to genera…
SpecRLBench: A Benchmark for Generalization in Specification-Guided Reinforcement Learning
Zijian Guo, İlker Işık, H. M. Sabbir Ahmad +1
Specification-guided reinforcement learning (RL) provides a principled framework for encoding complex, temporally extended tasks using formal specifications such as linear temporal…
Names Don't Matter: Symbol-Invariant Transformer for Open-Vocabulary Learning
İlker Işık, Wenchao Li
Current neural architectures lack a principled way to handle interchangeable tokens, i.e., symbols that are semantically equivalent yet distinguishable, such as bound variables. As…
One Subgoal at a Time: Zero-Shot Generalization to Arbitrary Linear Temporal Logic Requirements in Multi-Task Reinforcement Learning
Zijian Guo, İlker Işık, H. M. Sabbir Ahmad +1
Generalizing to complex and temporally extended task objectives and safety constraints remains a critical challenge in reinforcement learning (RL). Linear temporal logic (LTL) offe…
Interchangeable Token Embeddings for Extendable Vocabulary and Alpha-Equivalence
İlker Işık, Ramazan Gokberk Cinbis, Ebru Aydin Gol
Language models lack the notion of interchangeable tokens: symbols that are semantically equivalent yet distinct, such as bound variables in formal logic. This limitation prevents…
Learning to Estimate System Specifications in Linear Temporal Logic using Transformers and Mamba
İlker Işık, Ebru Aydin Gol, Ramazan Gokberk Cinbis
Temporal logic is a framework for representing and reasoning about propositions that evolve over time. It is commonly used for specifying requirements in various domains, including…
Optimal Policy Synthesis from A Sequence of Goal Sets with An Application to Electric Distribution System Restoration
İlker Işık, Onur Yigit Arpali, Ebru Aydin Gol
Motivated by the post-disaster distribution system restoration problem, in this paper, we study the problem of synthesizing the optimal policy for a Markov Decision Process (MDP) f…
Field Teams Coordination for Earthquake-Damaged Distribution System Energization
İlker Işık, Ebru Aydin Gol
The re-energization of electrical distribution systems in a post-disaster scenario is of grave importance as most modern infrastructure systems rely heavily on the presence of elec…