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
The development of more flexible and robust models for reasoning about systems in environments with potentially conflicting information is becoming more and more relevant in different contexts. In this direction, we recently introduced paraconsistent transition systems, i.e. transition systems whose transitions are tagged with a pair of weights, one standing for the degree of evidence that the transition exists, another weighting its potential non existence. Moreover, these structures were endowed with a modal logic [3] that was further formalised as an institution in [5]. This paper goes a step further, proposing an approach for the structured specification of paraconsistent transition processes, i.e. paraconsistent transition systems with initial states. The proposed approach is developed along the lines of [12], which introduced a complete methodology for (standard) reactive systems development building on the Sannella and Tarlecki stepwise implementation process. For this, we enrich the logic with dynamic modalities and hybrid features, and provide a pallet of constructors and abstractors to support the development process of paraconsistent processes along the entire design cycle.

Abstract
As a compact representation of joint probability distributions over a dependence graph of random variables, and a tool for modelling and reasoning in the presence of uncertainty, Bayesian networks are of great importance for artificial intelligence to combine domain knowledge, capture causal relationships, or learn from incomplete datasets. Known as a NP-hard problem in a classical setting, Bayesian inference pops up as a class of algorithms worth to explore in a quantum framework. This paper explores such a research direction and improves on previous proposals by a judicious use of the utility function in an entangled configuration. It proposes a completely quantum mechanical decision-making process with a proven computational advantage. A prototype implementation in Qiskit (a Python-based program development kit for the IBM Q machine) is discussed as a proof-of-concept.

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
Finite-State Automata (FSA) are foundations for modelling, synthesis, verification, and implementation of controllers for manufacturing systems. However, FSA are limited to represent emerging features in manufacturing, such as the ability to recognise and switch contexts. One option is to enrich FSA with parameters that carry details about the manufacturing, which may favour design and control. A parameter can be embedded either on transitions or states of an FSA, and each approach defines its own modelling framework, so that their comparison and integration are not straightforward, and they may lead to different control solutions, modelled, processed and implemented distinctly. In this paper, we show how to combine advantages from parameters in manufacturing the modelling and control. We initially present a background that allows to understand each parameterisation strategy. Then, we introduce a conversion method that translates a design-friendly model into a synthesis-efficient structure. Finally, we use the converted models is synthesis, highlighting their advantages. Examples are used throughout the paper to illustrate and compare our results and tooling support is also provided.

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.