Generating Believable Stories in Large Domains. - Bilal Kartal; John Koenig; Stephen J. Guy (Intelligent Narrative Technologies, 2013)

User-driven narrative variation in large story domains using monte carlo tree search. - Bilal Kartal; John Koenig; Stephen J. Guy (AAMAS, 2014)

Stochastic Tree Search with Useful Cycles for patrolling problems. - Bilal Kartal; Julio Godoy; Ioannis Karamouzas; Stephen J. Guy (ICRA, 2015)

Monte Carlo Tree Search for Multi-Robot Task Allocation. - Bilal Kartal; Ernesto Nunes; Julio Godoy; Maria L. Gini (AAAI, 2016)

Data Driven Sokoban Puzzle Generation with Monte Carlo Tree Search. - Bilal Kartal; Nick Sohre; Stephen J. Guy (AIIDE, 2016)

Stochastic Planning in Large Search Spaces. - Bilal Kartal (IJCAI, 2016)

Is multiagent deep reinforcement learning the answer or the question? A brief survey. - Pablo Hernandez-Leal; Bilal Kartal; Matthew E. Taylor (CoRR, 2018)

Using Monte Carlo Tree Search as a Demonstrator within Asynchronous Deep RL. - Bilal Kartal; Pablo Hernandez-Leal; Matthew E. Taylor (CoRR, 2018)

On Hard Exploration for Reinforcement Learning: A Case Study in Pommerman. - Chao Gao; Bilal Kartal; Pablo Hernandez-Leal; Matthew E. Taylor (AIIDE, 2019)

Agent Modeling as Auxiliary Task for Deep Reinforcement Learning. - Pablo Hernandez-Leal; Bilal Kartal; Matthew E. Taylor (AIIDE, 2019)

Terminal Prediction as an Auxiliary Task for Deep Reinforcement Learning. - Bilal Kartal; Pablo Hernandez-Leal; Matthew E. Taylor (AIIDE, 2019)

Action Guidance with MCTS for Deep Reinforcement Learning. - Bilal Kartal; Pablo Hernandez-Leal; Matthew E. Taylor (AIIDE, 2019)

Towers of Saliency: A Reinforcement Learning Visualization Using Immersive Environments. - Nathan Douglas; Dianna Yim; Bilal Kartal; Pablo Hernandez-Leal; Frank Maurer; Matthew E. Taylor (ISS, 2019)

A survey and critique of multiagent deep reinforcement learning. - Pablo Hernandez-Leal; Bilal Kartal; Matthew E. Taylor (Auton. Agents Multi Agent Syst., 2019)

Safer Deep RL with Shallow MCTS: A Case Study in Pommerman. - Bilal Kartal; Pablo Hernandez-Leal; Chao Gao; Matthew E. Taylor (CoRR, 2019)

Skynet: A Top Deep RL Agent in the Inaugural Pommerman Team Competition. - Chao Gao; Pablo Hernandez-Leal; Bilal Kartal; Matthew E. Taylor (CoRR, 2019)

Providing Uncertainty-Based Advice for Deep Reinforcement Learning Agents (Student Abstract). - Felipe Leno da Silva; Pablo Hernandez-Leal; Bilal Kartal; Matthew E. Taylor (AAAI, 2020)

Uncertainty-Aware Action Advising for Deep Reinforcement Learning Agents. - Felipe Leno da Silva; Pablo Hernandez-Leal; Bilal Kartal; Matthew E. Taylor (AAAI, 2020)

A Very Condensed Survey and Critique of Multiagent Deep Reinforcement Learning. - Pablo Hernandez-Leal; Bilal Kartal; Matthew E. Taylor (AAMAS, 2020)

Work in Progress: Temporally Extended Auxiliary Tasks. - Craig Sherstan; Bilal Kartal; Pablo Hernandez-Leal; Matthew E. Taylor (CoRR, 2020)

PredictionNet: Real-Time Joint Probabilistic Traffic Prediction for Planning, Control, and Simulation. - Alexey Kamenev; Lirui Wang; Ollin Boer Bohan; Ishwar Kulkarni; Bilal Kartal; Artem Molchanov; Stan Birchfield; David Nistér; Nikolai Smolyanskiy (ICRA, 2022)

Llama-Nemotron: Efficient Reasoning Models. - Akhiad Bercovich; Itay Levy; Izik Golan; Mohammad Dabbah; Ran El-Yaniv; Omri Puny; Ido Galil; Zach Moshe; Tomer Ronen; Najeeb Nabwani; Ido Shahaf; Oren Tropp; et al. (CoRR, 2025)

Orak: A Foundational Benchmark for Training and Evaluating LLM Agents on Diverse Video Games. - Dongmin Park; Minkyu Kim; Beongjun Choi; Junhyuck Kim; Keon Lee; Jonghyun Lee; Inkyu Park; Byeong-Uk Lee; Jaeyoung Hwang; Jaewoo Ahn; Ameya Sunil Mahabaleshwarkar; Bilal Kartal; et al. (CoRR, 2025)