2015
Autores
Agosta, G; Silvano, C; Cardoso, JMP; Hübner, M;
Publicação
PARMA-DITAM@HiPEAC
Abstract
2015
Autores
Plessl, C; Baz, DE; Cong, G; Cardoso, JMP; Veiga, L; Rauber, T;
Publicação
CSE
Abstract
2015
Autores
Silvano, C; Agosta, G; Bartolini, A; Beccari, A; Benini, L; Cardoso, JMP; Cavazzoni, C; Cmar, R; Martinovic, J; Palermo, G; Palkovic, M; Rohou, E; Sanna, N; Slaninova, K;
Publicação
2015 IEEE 18TH INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE AND ENGINEERING (CSE)
Abstract
The main goal of the ANTAREX project is to express by a Domain Specific Language (DSL) the application self-adaptivity and to runtime manage and autotune applications for green and heterogeneous High Performance Computing (HPC) systems up to the Exascale level. Key innovations of the project include the introduction of a separation of concerns between self-adaptivity strategies and application functionalities. The DSL approach will allow the definition of energy-efficiency, performance, and adaptivity strategies as well as their enforcement at runtime through application autotuning and resource and power management.
2015
Autores
El Baz, D; Cardoso, JMP; Rauber, T;
Publicação
Proceedings - IEEE 18th International Conference on Computational Science and Engineering, CSE 2015
Abstract
2015
Autores
Silvano, C; Agosta, G; Cardoso, JMP; Huebner, M;
Publicação
ACM International Conference Proceeding Series
Abstract
2015
Autores
Nogueira, PA; Rodrigues, R; Oliveira, E; Nacke, LE;
Publicação
WEB INTELLIGENCE
Abstract
With the rising research in emotionally believable agents, several advances in agent technology have been made, ranging from interactive virtual agents to emotional mechanism simulations and emotional agent architectures. However, creating an emotionally believable agent capable of emotional thought is still largely out of reach. It has been proposed that being able to accurately model human emotion would allow agents to mimic human behaviour while these models are studied to create more accurate theoretical models. In light of these challenges, we present a general method for human emotional state modelling in interactive environments. The proposed method employs a three-layered classification process to model the arousal and valence (i.e., hedonic) emotional components, based on four selected psychophysiological metrics. Additionally, we also developed a simplified version of our system for use in real-time systems and low-fidelity applications. The modelled emotional states by both approaches compared favourably with a manual approach following the current best practices reported in the literature while also improving on its predictive ability. The obtained results indicate we are able to accurately predict human emotional states, both in offline and online scenarios with varying levels of granularity; thus, providing a transversal method for modelling and reproducing human emotional profiles.
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