2,883 research outputs found
Agents for educational games and simulations
This book consists mainly of revised papers that were presented at the Agents for Educational Games and Simulation (AEGS) workshop held on May 2, 2011, as part of the Autonomous Agents and MultiAgent Systems (AAMAS) conference in Taipei, Taiwan. The 12 full papers presented were carefully reviewed and selected from various submissions. The papers are organized topical sections on middleware applications, dialogues and learning, adaption and convergence, and agent applications
Recent Advances in Multi-modal 3D Scene Understanding: A Comprehensive Survey and Evaluation
Multi-modal 3D scene understanding has gained considerable attention due to
its wide applications in many areas, such as autonomous driving and
human-computer interaction. Compared to conventional single-modal 3D
understanding, introducing an additional modality not only elevates the
richness and precision of scene interpretation but also ensures a more robust
and resilient understanding. This becomes especially crucial in varied and
challenging environments where solely relying on 3D data might be inadequate.
While there has been a surge in the development of multi-modal 3D methods over
past three years, especially those integrating multi-camera images (3D+2D) and
textual descriptions (3D+language), a comprehensive and in-depth review is
notably absent. In this article, we present a systematic survey of recent
progress to bridge this gap. We begin by briefly introducing a background that
formally defines various 3D multi-modal tasks and summarizes their inherent
challenges. After that, we present a novel taxonomy that delivers a thorough
categorization of existing methods according to modalities and tasks, exploring
their respective strengths and limitations. Furthermore, comparative results of
recent approaches on several benchmark datasets, together with insightful
analysis, are offered. Finally, we discuss the unresolved issues and provide
several potential avenues for future research
Consciosusness in Cognitive Architectures. A Principled Analysis of RCS, Soar and ACT-R
This report analyses the aplicability of the principles of consciousness developed in the ASys project to three of the most relevant cognitive architectures. This is done in relation to their aplicability to build integrated control systems and studying their support for general mechanisms of real-time consciousness.\ud
To analyse these architectures the ASys Framework is employed. This is a conceptual framework based on an extension for cognitive autonomous systems of the General Systems Theory (GST).\ud
A general qualitative evaluation criteria for cognitive architectures is established based upon: a) requirements for a cognitive architecture, b) the theoretical framework based on the GST and c) core design principles for integrated cognitive conscious control systems
Protecting privacy of users in brain-computer interface applications
Machine learning (ML) is revolutionizing research and industry. Many ML applications rely on the use of large amounts of personal data for training and inference. Among the most intimate exploited data sources is electroencephalogram (EEG) data, a kind of data that is so rich with information that application developers can easily gain knowledge beyond the professed scope from unprotected EEG signals, including passwords, ATM PINs, and other intimate data. The challenge we address is how to engage in meaningful ML with EEG data while protecting the privacy of users. Hence, we propose cryptographic protocols based on secure multiparty computation (SMC) to perform linear regression over EEG signals from many users in a fully privacy-preserving(PP) fashion, i.e., such that each individual's EEG signals are not revealed to anyone else. To illustrate the potential of our secure framework, we show how it allows estimating the drowsiness of drivers from their EEG signals as would be possible in the unencrypted case, and at a very reasonable computational cost. Our solution is the first application of commodity-based SMC to EEG data, as well as the largest documented experiment of secret sharing-based SMC in general, namely, with 15 players involved in all the computations
- …