Current Search: Mondesire, Sean (x)
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- Title
- SARP NET: A SECURE, ANONYMOUS, REPUTATION-BASED, PEER-TO-PEER NETWORK.
- Creator
-
Mondesire, Sean, Lee, Joohan, University of Central Florida
- Abstract / Description
-
Since the advent of Napster, the idea of peer-to-peer (P2P) architectures being applied to file-sharing applications has become popular, spawning other P2P networks like Gnutella, Morpheus, Kazaa, and BitTorrent. This growth in P2P development has nearly eradicated the idea of the traditional client-server structure in the file-sharing model, now placing emphasizes on faster query processing, deeper levels of decentralism, and methods to protect against copyright law violation. SARP Net is a...
Show moreSince the advent of Napster, the idea of peer-to-peer (P2P) architectures being applied to file-sharing applications has become popular, spawning other P2P networks like Gnutella, Morpheus, Kazaa, and BitTorrent. This growth in P2P development has nearly eradicated the idea of the traditional client-server structure in the file-sharing model, now placing emphasizes on faster query processing, deeper levels of decentralism, and methods to protect against copyright law violation. SARP Net is a secure, anonymous, decentralized, P2P overlay network that is designed to protect the activity of its users in its own file-sharing community. It is secure in the fact that public-key encryption is used to guard eavesdroppers during messages. The protocol guarantees user anonymity by incorporating message hopping from node to node to prevent any network observer from pinpointing the origin of any file query or shared-file source. To further enhance the system's security, a reputation scheme is incorporated to police nodes from malicious activity, maintain the overlay's topology, and enforce rules to protect node identity.
Show less - Date Issued
- 2006
- Identifier
- CFE0001264, ucf:46900
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0001264
- Title
- Complementary Layered Learning.
- Creator
-
Mondesire, Sean, Wu, Annie, Wiegand, Rudolf, Sukthankar, Gita, Proctor, Michael, University of Central Florida
- Abstract / Description
-
Layered learning is a machine learning paradigm used to develop autonomous robotic-based agents by decomposing a complex task into simpler subtasks and learns each sequentially. Although the paradigm continues to have success in multiple domains, performance can be unexpectedly unsatisfactory. Using Boolean-logic problems and autonomous agent navigation, we show poor performance is due to the learner forgetting how to perform earlier learned subtasks too quickly (favoring plasticity) or...
Show moreLayered learning is a machine learning paradigm used to develop autonomous robotic-based agents by decomposing a complex task into simpler subtasks and learns each sequentially. Although the paradigm continues to have success in multiple domains, performance can be unexpectedly unsatisfactory. Using Boolean-logic problems and autonomous agent navigation, we show poor performance is due to the learner forgetting how to perform earlier learned subtasks too quickly (favoring plasticity) or having difficulty learning new things (favoring stability). We demonstrate that this imbalance can hinder learning so that task performance is no better than that of a sub-optimal learning technique, monolithic learning, which does not use decomposition. Through the resulting analyses, we have identified factors that can lead to imbalance and their negative effects, providing a deeper understanding of stability and plasticity in decomposition-based approaches, such as layered learning.To combat the negative effects of the imbalance, a complementary learning system is applied to layered learning. The new technique augments the original learning approach with dual storage region policies to preserve useful information from being removed from an agent's policy prematurely. Through multi-agent experiments, a 28% task performance increase is obtained with the proposed augmentations over the original technique.
Show less - Date Issued
- 2014
- Identifier
- CFE0005213, ucf:50626
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0005213