### Browsing by Department "University of Exeter"

Now showing 1 - 3 of 3

###### Results Per Page

###### Sort Options

Item IEEE Access Special Section Editorial(IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2019-01-01) Wu, Yulei; Yan, Zheng; Choo, Kim Kwang Raymond; Yang, Laurence T.; University of Exeter; Department of Communications and Networking; University of Texas at San Antonio; Saint Francis Xavier UniversityInternet of Things (IoT) is increasingly common in our society and daily life, with applications ranging from personal devices (e.g., wearable devices such as Google Smartwatches) to smart home (e.g., smart TVs and Amazon Echo) to smart city/grid (e.g., unmanned aerial and/or ground vehicles), as well as in battlefield settings (e.g., Internet of Battlefield / Military Things). One corresponding trend associated with the increase in IoT devices, in terms of both number and diversity, is a significant increase in the volume, velocity, variety, variability, and value of the generated and resultant data (i.e., 5Vs of big data).Item Quantum work in the Bohmian framework(2018-01-30) Sampaio, R.; Suomela, S.; Ala-Nissila, T.; Anders, J.; Philbin, T. G.; Multiscale Statistical and Quantum Physics; University of Exeter; Department of Applied PhysicsAt nonzero temperature classical systems exhibit statistical fluctuations of thermodynamic quantities arising from the variation of the system's initial conditions and its interaction with the environment. The fluctuating work, for example, is characterized by the ensemble of system trajectories in phase space and, by including the probabilities for various trajectories to occur, a work distribution can be constructed. However, without phase-space trajectories, the task of constructing a work probability distribution in the quantum regime has proven elusive. Here we use quantum trajectories in phase space and define fluctuating work as power integrated along the trajectories, in complete analogy to classical statistical physics. The resulting work probability distribution is valid for any quantum evolution, including cases with coherences in the energy basis. We demonstrate the quantum work probability distribution and its properties with an exactly solvable example of a driven quantum harmonic oscillator. Animportant feature of the work distribution is its dependence on the initial statistical mixture of pure states, which is reflected in higher moments of the work. The proposed approach introduces a fundamentally different perspective on quantum thermodynamics, allowing full thermodynamic characterization of the dynamics of quantum systems, including the measurement process.Item Towards machines that understand people(American Association for Artificial Intelligence, 2023-09-04) Howes, Andrew; Jokinen, Jussi P. P.; Oulasvirta, A; University of Exeter; University of Jyväskylä; Department of Information and Communications EngineeringThe ability to estimate the state of a human partner is an insufficient basis on which to build cooperative agents. Also needed is an ability to predict how people adapt their behavior in response to an agent's actions. We propose a new approach based on computational rationality, which models humans based on the idea that predictions can be derived by calculating policies that are approximately optimal given human-like bounds. Computational rationality brings together reinforcement learning and cognitive modeling in pursuit of this goal, facilitating machine understanding of humans.