Zobrazeno 1 - 10
of 475
pro vyhledávání: '"Abate, Alessandro"'
Publikováno v:
Leibniz Transactions on Embedded Systems, Vol 8, Iss 2, Pp 0:i-0:iii (2022)
This special issue contains seven papers within the broad subject of Distributed Hybrid Systems, that is, systems combining hybrid discrete-continuous state spaces with elements of concurrency and logical or spatial distribution. It follows up on sev
Externí odkaz:
https://doaj.org/article/bd6ca138b48f4126a0204751e1b63a03
Autor:
Benjamin, Patrick, Abate, Alessandro
Recent works have provided algorithms by which decentralised agents, which may be connected via a communication network, can learn equilibria in Mean-Field Games from a single, non-episodic run of the empirical system. However, these algorithms are g
Externí odkaz:
http://arxiv.org/abs/2408.11607
We present a data-driven approach for learning MDP policies that are robust across stochastic environments whose transition probabilities are defined by parameters with an unknown distribution. We produce probably approximately correct (PAC) guarante
Externí odkaz:
http://arxiv.org/abs/2408.03093
The goal of Bayesian inverse reinforcement learning (IRL) is recovering a posterior distribution over reward functions using a set of demonstrations from an expert optimizing for a reward unknown to the learner. The resulting posterior over rewards c
Externí odkaz:
http://arxiv.org/abs/2407.10971
In reinforcement learning, specifying reward functions that capture the intended task can be very challenging. Reward learning aims to address this issue by learning the reward function. However, a learned reward model may have a low error on the tra
Externí odkaz:
http://arxiv.org/abs/2406.15753
Leveraging human preferences for steering the behavior of Large Language Models (LLMs) has demonstrated notable success in recent years. Nonetheless, data selection and labeling are still a bottleneck for these systems, particularly at large scale. H
Externí odkaz:
http://arxiv.org/abs/2406.10023
We present for the first time a supermartingale certificate for $\omega$-regular specifications. We leverage the Robbins & Siegmund convergence theorem to characterize supermartingale certificates for the almost-sure acceptance of Streett conditions
Externí odkaz:
http://arxiv.org/abs/2405.17304
We introduce a data-driven approach to computing finite bisimulations for state transition systems with very large, possibly infinite state space. Our novel technique computes stutter-insensitive bisimulations of deterministic systems, which we chara
Externí odkaz:
http://arxiv.org/abs/2405.15723
Abstractions of dynamical systems enable their verification and the design of feedback controllers using simpler, usually discrete, models. In this paper, we propose a data-driven abstraction mechanism based on a novel metric between Markov models. O
Externí odkaz:
http://arxiv.org/abs/2405.08353
We address the problem of characterising the aggregate flexibility in populations of electric vehicles (EVs) with uncertain charging requirements. Building on previous results that provide exact characterisations of the aggregate flexibility in popul
Externí odkaz:
http://arxiv.org/abs/2405.08232