3 citations · 3 across the 6 of their papers we have counts for
7 papers
Counterfactual Scenarios for Automated Planning
Nicola Gigante, Francesco Leofante, Andrea Micheli
Counterfactual Explanations (CEs) are a powerful technique used to explain Machine Learning models by showing how the input to a model should be minimally changed for the model to…
Platform-Aware Mission Planning
Stefan Panjkovic, Alessandro Cimatti, Andrea Micheli +1
Planning for autonomous systems typically requires reasoning with models at different levels of abstraction, and the harmonization of two competing sets of objectives: high-level m…
Formal Analysis and Verification of Max-Plus Linear Systems
Muhammad Syifa'ul Mufid, Andrea Micheli, Alessandro Abate +1
Max-Plus Linear (MPL) systems are an algebraic formalism with practical applications in transportation networks, manufacturing and biological systems. In this paper, we investigate…
An Efficient Incremental Simple Temporal Network Data Structure for Temporal Planning
Andrea Micheli
One popular technique to solve temporal planning problems consists in decoupling the causal decisions, demanding them to heuristic search, from temporal decisions, demanding them t…
Towards Efficient Anytime Computation and Execution of Decoupled Robustness Envelopes for Temporal Plans
Michael Cashmore, Alessandro Cimatti, Daniele Magazzeni +2
One of the major limitations for the employment of model-based planning and scheduling in practical applications is the need of costly re-planning when an incongruence between the…
Temporal Planning with Intermediate Conditions and Effects
Alessandro Valentini, Andrea Micheli, Alessandro Cimatti
Automated temporal planning is the technology of choice when controlling systems that can execute more actions in parallel and when temporal constraints, such as deadlines, are nee…