The paper introduces a method for numerical Totally-Ordered HTN (TOHTN) planning by extending standard SAT-based encodings with SMT to handle numeric fluents. It also presents a new benchmark suite for evaluating numerical TOHTN planning, providing a common basis for future research. Experimental results demonstrate that this straightforward encoding serves as a competitive baseline for the field.
By Gaspard Quenard, Takudzwa Togarepi, Damien Pellier, Humbert Fiorino
The paper evaluates strategies for increasing plan‑execution flexibility by converting sequential plans into partial‑order plans through deordering and reordering. It compares block deordering methods, which restructure causal dependencies, with MaxSAT‑based approaches that optimize within existing causal structures. The study finds that block deordering consistently outperforms MaxSAT in both effectiveness and efficiency, offering anytime solutions and higher flexibility gains per computation time.
By Md. Monjurul Islam, Sabah Binte Noor, Fazlul Hasan Siddiqui, Gahangir Hossain
arXiv:2607. 25484v1 Announce Type: new Abstract: In some real applications a plan may later become unfeasible due to newly imposed budget constraints, yet, at the same time, using only the original actions of the plan and their order is mandatory.
By Martha Del Toro, Raquel Fuentetaja, Angel Garc\'ia-Olaya
arXiv:2606. 06300v1 Announce Type: new Abstract: We propose MResOpt, a staged residual neural network architecture for constrained optimization problems.
By Merve Karakas, Christopher J. Williams, Emmanuel O. Balogun, Sadegh Sadeghi Tabas, Christian Brown, Nikhil Rao
arXiv:2603.08814v2 Announce Type: replace-cross
Abstract: Long-horizon task planning for heterogeneous multi-robot systems is essential for deploying collaborative teams in real-world environments; y...
By Piyush Gupta, Sangjae Bae, Jiachen Li, David Isele
arXiv:2607. 17973v1 Announce Type: new Abstract: Latent world models have emerged as a powerful planning paradigm by learning action-conditioned predictive dynamics and using them as internal simulators to imagine and evaluate candidate action sequences.
By Letian Cheng, Qi Zhang, Yisen Wang