Abstract
Variational quantum circuits are being used as versatile quantum machine learning models. Some empirical results exhibit an advantage in supervised and generative learning tasks. However, when applied to reinforcement learning, less is known. In this work, we considered a variational quantum circuit composed of a low-depth hardware-efficient ansatz as the parameterized policy of a reinforcement learning agent. We show that an epsilon-approximation of the policy gradient can be obtained using a logarithmic number of samples concerning the total number of parameters. We empirically verify that such quantum models behave similarly to typical classical neural networks used in standard benchmarking environments and quantum control, using only a fraction of the parameters. Moreover, we study the barren plateau phenomenon in quantum policy gradients using the Fisher information matrix spectrum.

Abstract

Abstract
This paper introduces a class of automata and associated languages, suitable to model a computational paradigm of fuzzy systems, in which both vagueness and simultaneity are taken as first-class citizens. This requires a weighted semantics for transitions and a precise notion of a synchronous product to enforce the simultaneous occurrence of actions. The usual relationships between automata and languages are revisited in this setting, including a specific Kleene theorem.

Abstract
Secure Multiparty Computation (SMC) enables multiple parties to cooperate securely without compromising their privacy. SMC has the potential to offer solutions for privacy obstacles in vehicular networks. However, classical SMC implementations suffer from efficiency and security challenges. To address this problem, two quantum communication technologies, Quantum Key Distribution (QKD) and Quantum Oblivious Key Distribution were utilised. These technologies supply symmetric and oblivious keys respectively, allowing fast and secure inter-vehicular communications. These quantum technologies are integrated with the Faster Malicious Arithmetic Secure Computation with Oblivious Transfer (MASCOT) protocol to form a Quantum Secure Multiparty Computation (QSMC) platform. A lane change service is implemented in which vehicles broadcast private information about their intention to exit the highway. The proposed QSMC approach provides unconditional security even against quantum computer attacks. Moreover, the communication cost of the quantum approach for the lane change use case has decreased by 97% when compared to the classical implementation. However, the computation cost has increased by 42%. For open space scenarios, the reduction in communication cost is especially important, because it conserves bandwidth in the free-space radio channel, outweighing the increase in computation cost. A Quantum Secure Multiparty Computation (QSMC) solution for lane change service in vehicular networks that uses two quantum technologies, Quantum Key Distribution (QKD) and Quantum Oblivious Key Distribution (QOKD) is proposed. This quantum-based approach is resistant to quantum computer attacks and requires less communication resources compared to classical methods.image

Abstract
This paper sets the basis for a compositional and structured approach to the specification of paraconsistent transitions systems, framed as an institution. The latter and theirs logics were previously introduced in [CMB22] to deal with scenarios of inconsistency in which several requirements are on stake, either reinforcing or contradicting each other. © 2023, IFIP International Federation for Information Processing.

Abstract
This position paper builds on the authors' previous work on paraconsistent transition systems to propose a modelling framework for quantum circuits with explicit representation of decoherence.