All Outputs (75)

Towards Better Understanding the Challenges of Reliable and Trust-Aware Critical Communications in the Aftermath of Disaster (2018)
Conference Proceeding
Radenkovic, M., Walker, A., & Bai, L. (2018). Towards Better Understanding the Challenges of Reliable and Trust-Aware Critical Communications in the Aftermath of Disaster. In IWCMC 2018: the 14th International Wireless Communications & Mobile Computing Conference (648-653). https://doi.org/10.1109/IWCMC.2018.8450430

This paper seeks to better understand the highly multi-dimensional, multi-faceted challenges of meeting trust and reliability requirements in critical, disaster aftermath communication networks comprising heterogeneous groups of sensor equipped nodes... Read More about Towards Better Understanding the Challenges of Reliable and Trust-Aware Critical Communications in the Aftermath of Disaster.

Risk sensitive decision making using type reduction methods (2018)
Conference Proceeding
Runkler, T. A., Chen, C., & John, R. (in press). Risk sensitive decision making using type reduction methods. In Proceedings. 28. Workshop Computational Intelligence, Dortmund, 29. - 30. November 2018

From clusters to queries: exploiting uncertainty in the modularity landscape of complex networks (2018)
Conference Proceeding
Gilbert, J. P., & Twycross, J. (2018). From clusters to queries: exploiting uncertainty in the modularity landscape of complex networks.

Uncovering latent community structure in complex networks is a field that has received an enormous amount of attention. Unfortunately, whilst potentially very powerful, unsupervised methods for uncovering labels based on topology alone has been shown... Read More about From clusters to queries: exploiting uncertainty in the modularity landscape of complex networks.

Getting more out of Stan: some ideas from the Haskell bindings (2018)
Conference Proceeding
NILSSON, H., NIELSEN, T. A., & STEINITZ, D. (2018). Getting more out of Stan: some ideas from the Haskell bindings

Stan has emerged as the most practical and widely used probabilistic programming language for Bayesian computation. As the capabilities within Stan for further processing of results from probabilistic computations is limited, Stan is often used from... Read More about Getting more out of Stan: some ideas from the Haskell bindings.

Incentive-compatible mechanisms for norm monitoring in open multi-agent systems (Extended abstract) (2018)
Conference Proceeding
Alechina, N., Halpern, J. Y., Kash, I. A., & Logan, B. (2018). Incentive-compatible mechanisms for norm monitoring in open multi-agent systems (Extended abstract). In Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence. https://doi.org/10.24963/ijcai.2018/781

We consider the problem of detecting norm violations in open multi-agent systems (MAS). In this extended abstract, we outline the approach of [Alechina et al., 2018], and show how, using ideas from scrip systems, we can design mecha... Read More about Incentive-compatible mechanisms for norm monitoring in open multi-agent systems (Extended abstract).

An operational semantics for a fragment of PRS (2018)
Conference Proceeding
de Silva, L., Meneguzzi, F., & Logan, B. (2018). An operational semantics for a fragment of PRS.

The Procedural Reasoning System (PRS) is arguably the first implementation of the Belief–Desire–Intention (BDI) approach to agent programming. PRS remains extremely influential, directly or indirectly inspiring the development of subsequent BDI agent p... Read More about An operational semantics for a fragment of PRS.

Resource logics with a diminishing resource: extended abstract (2018)
Conference Proceeding
Alechina, N., & Logan, B. (2018). Resource logics with a diminishing resource: extended abstract. In Proceedings of the 17th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2018)

Model-checking resource logics with production and consumption of resources is a computationally hard and often undecidable problem. We show that it is more feasible under the assumption that there is at least one diminishing resource, that is, a res... Read More about Resource logics with a diminishing resource: extended abstract.

Exploring subsethood to determine firing strength in non-singleton fuzzy logic systems (2018)
Conference Proceeding
Pekaslan, D., Garibaldi, J. M., & Wagner, C. (2018). Exploring subsethood to determine firing strength in non-singleton fuzzy logic systems.

Real world environments face a wide range of sources of noise and uncertainty. Thus, the ability to handle various uncertainties, including noise, becomes an indispensable element of automated decision making. Non-Singleton Fuzzy Logic Systems (NSFLS... Read More about Exploring subsethood to determine firing strength in non-singleton fuzzy logic systems.

Composite capabilities for cloud manufacturing (demonstration) (2018)
Conference Proceeding
Felli, P., de Silva, L., Logan, B., & Ratchev, S. (2018). Composite capabilities for cloud manufacturing (demonstration).

A Preliminary Study of the Feasibility of Global Evolutionary Feature Selection for Big Datasets under Apache Spark (2018)
Conference Proceeding
Galar, M., Triguero, I., Bustince, H., & Herrera, F. (2018). A Preliminary Study of the Feasibility of Global Evolutionary Feature Selection for Big Datasets under Apache Spark. In 2018 IEEE Congress on Evolutionary Computation (CEC) - Proceedings (1-8). https://doi.org/10.1109/CEC.2018.8477878

Designing efficient learning models capable of dealing with tons of data has become a reality in the era of big data. However, the amount of available data is too much for traditional data mining techniques to be applicable. This issue is even more s... Read More about A Preliminary Study of the Feasibility of Global Evolutionary Feature Selection for Big Datasets under Apache Spark.

A genetic algorithm with composite chromosome for shift assignment of part-time employees (2018)
Conference Proceeding
Xue, N., Landa-Silva, D., Triguero, I., & Figueredo, G. P. (2018). A genetic algorithm with composite chromosome for shift assignment of part-time employees.

Personnel scheduling problems involve multiple tasks, including assigning shifts to workers. The purpose is usually to satisfy objectives and constraints arising from management, labour unions and employee preferences. The shift assignment problem is... Read More about A genetic algorithm with composite chromosome for shift assignment of part-time employees.

Learning in reproducing kernel Kreın spaces (2018)
Conference Proceeding
Oglic, D., & Gärtner, T. (2018). Learning in reproducing kernel Kreın spaces.

We formulate a novel regularized risk minimization problem for learning in reproducing kernel Kreın spaces and show that the strong representer theorem applies to it. As a result of the latter, the learning problem can be expressed as the minimizatio... Read More about Learning in reproducing kernel Kreın spaces.

Free Higher Groups in Homotopy Type Theory (2018)
Conference Proceeding
Kraus, N., & Altenkirch, T. (2018). Free Higher Groups in Homotopy Type Theory. In LICS '18: Proceedings of the 33rd Annual ACM/IEEE Symposium on Logic in Computer Science (599-608). https://doi.org/10.1145/3209108.3209183

© 2018 ACM. Given a type A in homotopy type theory (HoTT), we can define the free∞-group onA as the loop space of the suspension ofA+1. Equivalently, this free higher group can be defined as a higher inductive type F(A) with constructors unit : F(A),... Read More about Free Higher Groups in Homotopy Type Theory.

Exploring Constrained Type-2 fuzzy sets (2018)
Conference Proceeding
D’Alterio, P., Garibaldi, J. M., & Pourabdollah, A. (2018). Exploring Constrained Type-2 fuzzy sets.

Fuzzy logic has been widely used to model human reasoning thanks to its inherent capability of handling uncertainty. In particular, the introduction of Type-2 fuzzy sets added the possibility of expressing uncertainty even on the definition of the me... Read More about Exploring Constrained Type-2 fuzzy sets.

Direct Application of Convolutional Neural Network Features to Image Quality Assessment (2018)
Conference Proceeding
Hou, X., Sun, K., Liu, B., Gong, Y., Garibaldi, J., & Qiu, G. (2018). Direct Application of Convolutional Neural Network Features to Image Quality Assessment. In 2018 IEEE Visual Communications and Image Processing (VCIP). https://doi.org/10.1109/VCIP.2018.8698726

© 2018 IEEE. We take advantage of the popularity of deep con-volutional neural networks (CNNs) and have developed a very simple image quality assessment method that rivals state of the art. We show that convolutional layer outputs (deep features) of... Read More about Direct Application of Convolutional Neural Network Features to Image Quality Assessment.

Cinema-going trajectories in the digital age (2018)
Conference Proceeding
Styliari, T. C., Kefalidou, G., & Koleva, B. (2018). Cinema-going trajectories in the digital age.

The activity of cinema-going constantly evolves and gradually integrates the use of digital data and platforms to become more engaging for the audiences. Combining methods from the fields of Human Computer Interaction and Film Studies, we conducted t... Read More about Cinema-going trajectories in the digital age.

Understanding complementary multi-layer collaborative heuristics for adaptive caching in heterogeneous mobile opportunistic networks (2018)
Conference Proceeding
Huynh, V. S. H., & Radenkovic, M. (2018). Understanding complementary multi-layer collaborative heuristics for adaptive caching in heterogeneous mobile opportunistic networks.

Current research aims to deal with emerging challenges of the opportunistic discovery of content stored in remote mobile publishers and the delivery to the subscribers in heterogeneous mobile opportunistic networks. Innovative network and service arc... Read More about Understanding complementary multi-layer collaborative heuristics for adaptive caching in heterogeneous mobile opportunistic networks.

Understanding information centric layer of adaptive collaborative caching framework in mobile disconnection-prone networks (2018)
Conference Proceeding
Huynh, V. S. H., Radenkovic, M., & John, R. (2018). Understanding information centric layer of adaptive collaborative caching framework in mobile disconnection-prone networks.

Smart networks and services leverage in-network caching to improve transmission efficiency and support large amount of content sharing, decrease high operating costs and handle disconnections. In this paper, we investigate the complex challenges rela... Read More about Understanding information centric layer of adaptive collaborative caching framework in mobile disconnection-prone networks.

CognitiveCharge: disconnection tolerant adaptive collaborative and predictive vehicular charging (2018)
Conference Proceeding
Radenkovic, M., & Walker, A. (2018). CognitiveCharge: disconnection tolerant adaptive collaborative and predictive vehicular charging.

Electric vehicles (EVs) are rapidly becoming more common and ownership is set to rise globally in coming years. The potential impacts of increased EVs on the electrical grid have been widely investigated and in its current state, existing grid infras... Read More about CognitiveCharge: disconnection tolerant adaptive collaborative and predictive vehicular charging.

Explicating the challenges of providing novel media experiences driven by user personal data (2018)
Conference Proceeding
Sailaja, N., Crabtree, A., McAuley, D., & Stenton, P. (2018). Explicating the challenges of providing novel media experiences driven by user personal data. In TVX '18 Proceedings of the 2018 ACM International Conference on Interactive Experiences for TV and Online Video (101-113). https://doi.org/10.1145/3210825.3210830

The turn towards personal data to drive novel media experiences has resulted in a shift in the priorities and challenges associated with media creation and dissemination. This paper takes up the challenge of explicating this novel and dynamic scenari... Read More about Explicating the challenges of providing novel media experiences driven by user personal data.