13 papers
Hierarchical Soft Actor-Critic for Sparse-Reward Long-Horizon Reinforcement Learning
Zahra Abdalla Elashaal, Afef Hfaiedh, Nahla Khraief +2
Exploration in sparse-reward long-horizon tasks poses significant challenges for reinforcement learning. To address these challenges, we propose a two-level Hierarchical Reinforcem…
When is the combined load identifiable from a stress-intensity profile? A coupled forward-inverse study on SIFBench finite-element data
Giansalvo Cirrincione, Filippo Grassia
This work studies the inverse problem of recovering the relative magnitudes of the tension, bending, and bearing loads acting on a crack from its stress-intensity-factor profile al…
Incremental Transformer for Surrogate-Based Inverse Design of Geopolymer Mixtures
Giansalvo Cirrincione, Filippo Grassia
Small-data inverse design is challenging in engineering informatics when observations are heterogeneous, mixed-type, and constrained by physical relations among design variables. T…
Learned Lyapunov Shielding for Adaptive Control
Giansalvo Cirrincione, Adriano Fagiolini
We augment the Slotine--Li adaptive controller for Euler--Lagrange systems with three learned components: a structured-quadratic Lyapunov function \(V_Ï\) whose positive-definiten…
Temporal Attention for Adaptive Control of Euler-Lagrange Systems with Unobservable Memory
Giansalvo Cirrincione, Adriano Fagiolini
Adaptive control of Euler-Lagrange systems is challenging when friction is governed by a finite-horizon internal state that is not directly observable from joint measurements. In t…
Rank, Head-Channel Non-Identifiability, and Symmetry Breaking: A Precise Analysis of Representational Collapse in Transformers
Giansalvo Cirrincione
A widely cited result by Dong et al. (2021) showed that Transformers built from self-attention alone, without skip connections or feed-forward layers, suffer from rapid rank collap…