Deceptive Level Generation for Angry Birds. - Chathura Nagoda Gamage; Vimukthini Pinto; Jochen Renz; Matthew Stephenson (CoG, 2021)

Novelty Generation Framework for AI Agents in Angry Birds Style Physics Games. - Chathura Nagoda Gamage; Vimukthini Pinto; Cheng Xue; Matthew Stephenson; Peng Zhang 021; Jochen Renz (CoG, 2021)

The Difficulty of Novelty Detection in Open-World Physical Domains: An Application to Angry Birds. - Vimukthini Pinto; Cheng Xue; Chathura Nagoda Gamage; Jochen Renz (CoRR, 2021)

Phy-Q: A Benchmark for Physical Reasoning. - Cheng Xue; Vimukthini Pinto; Chathura Nagoda Gamage; Ekaterina Nikonova; Peng Zhang 021; Jochen Renz (CoRR, 2021)

Measuring Difficulty of Novelty Reaction. - Ekaterina Nikonova; Cheng Xue; Vimukthini Pinto; Chathura Nagoda Gamage; Peng Zhang 021; Jochen Renz (CoRR, 2022)

Physics-Based Task Generation through Causal Sequence of Physical Interactions. - Chathura Nagoda Gamage; Vimukthini Pinto; Matthew Stephenson; Jochen Renz (AIIDE, 2023)

The Difficulty of Novelty Detection and Adaptation in Physical Environments. - Vimukthini Pinto; Chathura Nagoda Gamage; Matthew Stephenson; Jochen Renz (AI (2), 2023)

NovPhy: A Testbed for Physical Reasoning in Open-world Environments. - Chathura Nagoda Gamage; Vimukthini Pinto; Cheng Xue; Peng Zhang 021; Ekaterina Nikonova; Matthew Stephenson; Jochen Renz (CoRR, 2023)

Phy-Q as a measure for physical reasoning intelligence. - Cheng Xue; Vimukthini Pinto; Chathura Nagoda Gamage; Ekaterina Nikonova; Peng Zhang 021; Jochen Renz (Nat. Mac. Intell., 2023)

A comparison of Bayesian Markov chain Monte Carlo methods in a multilevel scenario. - Darshika Karunarasan; Roshini Sooriyarachchi; Vimukthini Pinto (Commun. Stat. Simul. Comput., 2023)

NovPhy: A physical reasoning benchmark for open-world AI systems. - Vimukthini Pinto; Chathura Nagoda Gamage; Cheng Xue; Peng Zhang 021; Ekaterina Nikonova; Matthew Stephenson; Jochen Renz (Artif. Intell., 2024)