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- BDI architecture (1)
- CSMA (1)
- Design of experiments (1)
- Energy harvesting (1)
- Instance clustering (1)
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- Instance-based automated tuning parameter (1)
- Medium access control (1)
- Minefield navigation (1)
- Parameter tuning algorithm (1)
- Plan learning (1)
- Probabilistic polling (1)
- Reinforcement learning (1)
- Response surface methodology (1)
- Search trajectory (1)
- Self-organizing neural networks (1)
- Sequence alignment (1)
- Underwater localization; Acoustic communications; Underwater sensor networks (1)
- Wireless sensor networks (1)
Articles 1 - 7 of 7
Full-Text Articles in Engineering
A Survey Of Techniques And Challenges In Underwater Localization, Hwee-Pink Tan, Roee Diamant, Winston K. G. Seah, Marc Waldmeyer
A Survey Of Techniques And Challenges In Underwater Localization, Hwee-Pink Tan, Roee Diamant, Winston K. G. Seah, Marc Waldmeyer
Research Collection School Of Computing and Information Systems
Underwater Wireless Sensor Networks (UWSNs) are expected to support a variety of civilian and military applications. Sensed data can only be interpreted meaningfully when referenced to the location of the sensor, making localization an important problem. While global positioning system (GPS) receivers are commonly used in terrestrial WSNs to achieve this, this is infeasible in UWSNs as GPS signals do not propagate through water. Acoustic communications is the most promising mode of communication underwater. However, underwater acoustic channels are characterized by harsh physical layer conditions with low bandwidth, high propagation delay and high bit error rate. Moreover, the variable speed …
A Hybrid Agent Architecture Integrating Desire, Intention And Reinforcement Learning, Ah-Hwee Tan, Yew-Soon Ong, Akejariyawong Tapanuj
A Hybrid Agent Architecture Integrating Desire, Intention And Reinforcement Learning, Ah-Hwee Tan, Yew-Soon Ong, Akejariyawong Tapanuj
Research Collection School Of Computing and Information Systems
This paper presents a hybrid agent architecture that integrates the behaviours of BDI agents, specifically desire and intention, with a neural network based reinforcement learner known as Temporal DifferenceFusion Architecture for Learning and COgNition (TD-FALCON). With the explicit maintenance of goals, the agent performs reinforcement learning with the awareness of its objectives instead of relying on external reinforcement signals. More importantly, the intention module equips the hybrid architecture with deliberative planning capabilities, enabling the agent to purposefully maintain an agenda of actions to perform and reducing the need of constantly sensing the environment. Through reinforcement learning, plans can also be …
Design And Performance Analysis Of Mac Schemes For Wireless Sensor Networks Powered By Ambient Energy Harvesting, Zhi Ang Eu, Hwee-Pink Tan, Winston K. G. Seah
Design And Performance Analysis Of Mac Schemes For Wireless Sensor Networks Powered By Ambient Energy Harvesting, Zhi Ang Eu, Hwee-Pink Tan, Winston K. G. Seah
Research Collection School Of Computing and Information Systems
Energy consumption is a perennial issue in the design of wireless sensor networks (WSNs) which typically rely on portable sources like batteries for power. Recent advances in ambient energy harvesting technology have made it a potential and promising alternative source of energy for powering WSNs. By using energy harvesters with supercapacitors, WSNs are able to operate perpetually until hardware failure and in places where batteries are hard or impossible to replace. In this paper, we study the performance of different medium access control (MAC) schemes based on CSMA and polling techniques for WSNs which are solely powered by ambient energy …
Interactivity-Constrained Server Provisioning In Large-Scale Distributed Virtual Environments, Nguyen Binh Duong Ta, Thang Nguyen, Suiping Zhou, Xueyan Tang, Wentong Cai, Rassul Ayani
Interactivity-Constrained Server Provisioning In Large-Scale Distributed Virtual Environments, Nguyen Binh Duong Ta, Thang Nguyen, Suiping Zhou, Xueyan Tang, Wentong Cai, Rassul Ayani
Research Collection School Of Computing and Information Systems
Maintaining interactivity is one of the key challenges in distributed virtual environments (DVE), e.g., online games, distributed simulations, etc., due to the large, heterogeneous Internet latencies; and the fact that clients in a DVE are usually geographically separated. In this paper, we consider a new problem, termed the interactivity-constrained server provisioning problem, whose goal is to minimize the number of distributed servers needed to achieve a pre-determined level of interactivity. We identify and formulate two variants of this new problem and show that they are both NP-hard via reductions to the set covering problem. We then propose several computationally efficient …
A High-Throughput Routing Metric For Reliable Multicast In Multi-Rate Wireless Mesh Networks, Xin Zhao, Jun Guo, Chun Tung Chou, Archan Misra, Sanjay Jha
A High-Throughput Routing Metric For Reliable Multicast In Multi-Rate Wireless Mesh Networks, Xin Zhao, Jun Guo, Chun Tung Chou, Archan Misra, Sanjay Jha
Research Collection School Of Computing and Information Systems
We propose a routing metric for enabling highthroughput reliable multicast in multi-rate wireless mesh networks. This new multicast routing metric, called expected multicast transmission time (EMTT), captures the combined effects of 1) MAC-layer retransmission-based reliability, 2) transmission rate diversity, 3) wireless broadcast advantage, and 4) link quality awareness. The EMTT of one-hop transmission of a multicast packet minimizes the amount of expected transmission time (including that required for retransmissions). This is achieved by allowing the sender to adapt its bit-rate for each ongoing transmission/retransmission, optimized exclusively for its nexthop receivers that have not yet received the multicast packet. We model …
Instance-Based Parameter Tuning Via Search Trajectory Similarity Clustering, Linda Lindawati, Hoong Chuin Lau, David Lo
Instance-Based Parameter Tuning Via Search Trajectory Similarity Clustering, Linda Lindawati, Hoong Chuin Lau, David Lo
Research Collection School Of Computing and Information Systems
This paper is concerned with automated tuning of parameters in local-search based meta-heuristics. Several generic approaches have been introduced in the literature that returns a ”one-size-fits-all” parameter configuration for all instances. This is unsatisfactory since different instances may require the algorithm to use very different parameter configurations in order to find good solutions. There have been approaches that perform instance-based automated tuning, but they are usually problem-specific. In this paper, we propose CluPaTra, a generic (problem-independent) approach to perform parameter tuning, based on CLUstering instances with similar PAtterns according to their search TRAjectories. We propose representing a search trajectory as …
Fine-Tuning Algorithm Parameters Using The Design Of Experiments Approach, Aldy Gunawan, Hoong Chuin Lau, Linda Lindawati
Fine-Tuning Algorithm Parameters Using The Design Of Experiments Approach, Aldy Gunawan, Hoong Chuin Lau, Linda Lindawati
Research Collection School Of Computing and Information Systems
Optimizing parameter settings is an important task in algorithm design. Several automated parameter tuning procedures/configurators have been proposed in the literature, most of which work effectively when given a good initial range for the parameter values. In the Design of Experiments (DOE), a good initial range is known to lead to an optimum parameter setting. In this paper, we present a framework based on DOE to find a good initial range of parameter values for automated tuning. We use a factorial experiment design to first screen and rank all the parameters thereby allowing us to then focus on the parameter …