Open Access. Powered by Scholars. Published by Universities.®
- Keyword
-
- Uncertainty (3)
- Lagrangian Relaxation (2)
- Multi-Agent Systems (2)
- 802.11 (1)
- Adaptive maintenance advisor (1)
-
- Adaptive resonance theory (1)
- Agent-based model (1)
- Air indices (1)
- AoA (1)
- ArrayTrack (1)
- Artificial Intelligence (1)
- Auction (1)
- Autonomous Learning 2012 (1)
- Autonomous trading (1)
- Bid pricing behavior (1)
- Celebrity videos (1)
- Census (1)
- Commodity trading (1)
- Community analysis (1)
- Computer Science (1)
- Continuous activity recognition (1)
- Cross-domain concept learning (1)
- DCOP (1)
- DEC-POMDP (1)
- DPOP (1)
- Database (1)
- De-anonymization (1)
- Delayed Observations (1)
- Domain adaptation (1)
- Energy efficient learning (1)
Articles 31 - 37 of 37
Full-Text Articles in Engineering
Extreme Learning Machine Terrain-Based Navigation For Unmanned Aerial Vehicles, Ee May Kan, Meng Hiot Lim, Yew Soon Ong, Ah-Hwee Tan, Swee Ping Yeo
Extreme Learning Machine Terrain-Based Navigation For Unmanned Aerial Vehicles, Ee May Kan, Meng Hiot Lim, Yew Soon Ong, Ah-Hwee Tan, Swee Ping Yeo
Research Collection School Of Computing and Information Systems
Unmanned aerial vehicles (UAVs) rely on global positioning system (GPS) information to ascertain its position for navigation during mission execution. In the absence of GPS information, the capability of a UAV to carry out its intended mission is hindered. In this paper, we learn alternative means for UAVs to derive real-time positional reference information so as to ensure the continuity of the mission. We present extreme learning machine as a mechanism for learning the stored digital elevation information so as to aid UAVs to navigate through terrain without the need for GPS. The proposed algorithm accommodates the need of the …
Self‐Regulating Action Exploration In Reinforcement Learning, Teck-Hou Teng, Ah-Hwee Tan, Yuan-Sin Tan
Self‐Regulating Action Exploration In Reinforcement Learning, Teck-Hou Teng, Ah-Hwee Tan, Yuan-Sin Tan
Research Collection School Of Computing and Information Systems
The basic tenet of a learning process is for an agent to learn for only as much and as long as it is necessary. With reinforcement learning, the learning process is divided between exploration and exploitation. Given the complexity of the problem domain and the randomness of the learning process, the exact duration of the reinforcement learning process can never be known with certainty. Using an inaccurate number of training iterations leads either to the non-convergence or the over-training of the learning agent. This work addresses such issues by proposing a technique to self-regulate the exploration rate and training duration …
Preface: Trends In Natural And Machine Intelligence, Jonathan H. Chan, Ah-Hwee Tan
Preface: Trends In Natural And Machine Intelligence, Jonathan H. Chan, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
Trends in natural and machine intelligence are increasingly reflecting a convergence in these two well-established fields of study. The Third International Neural Network Society Winter Conference (INNS-WC 2012) was held in Bangkok, Thailand, on October 3-5, 2012. INNS-WC2012, with an aim to bring together scientists, practitioners, and students worldwide, to discuss the past, present, and future challenges and trends in the area of natural and machine intelligence. This event has been a bi-annual conference of the International Neural Network Society (INNS) to provide a forum for international researchers to exchange latest ideas and advances on neural networks and related discipline.
Multi-Party Multi-Period Supply Chain Coordination, Thin Yin Leong, Michelle Lee Fong Cheong
Multi-Party Multi-Period Supply Chain Coordination, Thin Yin Leong, Michelle Lee Fong Cheong
Research Collection School Of Computing and Information Systems
We apply combinatorial auction as a coordination mechanism to smooth demands placed on suppliers' limited production capacities, allowing several manufacturers to share common suppliers effectively. Products are bidders bidding for parts from suppliers, consuming their capacities in different time periods. The fourth party logistic (4PL) provider acts as the auctioneer to coordinate bids and perform price iterations. We leverage on the strong links between the Lagrangian relaxation method and combinatorial auction, where the Lagrange multipliers serve as the supply capacity reserve prices, to balance the demand and supply of capacities. To prevent cyclic behaviour and to increase convergence speed, we …
A Sentiment Analysis Of Singapore Presidential Election 2011 Using Twitter Data With Census Correction, Murphy Junyu Choy, Michelle Lee Fong Cheong, Nang Laik Ma, Ping Shung Koo
A Sentiment Analysis Of Singapore Presidential Election 2011 Using Twitter Data With Census Correction, Murphy Junyu Choy, Michelle Lee Fong Cheong, Nang Laik Ma, Ping Shung Koo
Research Collection School Of Computing and Information Systems
Sentiment analysis is a new area in text analytics where it focuses on the analysis and understanding of the human emotions from the text patterns. This new form of analysis has been widely adopted in customer relationship management especially in the context of complaint management. However, sentiment analysis using Twitter data has remained extremely difficult to manage due to sampling biasness. In this paper, we will discuss about the application of reweighting techniques in conjunction with online sentiment divisions to predict the vote percentage that individual presidential candidate in Singapore will receive in the Presidential Election 2011. There will be …
Robust Local Search For Solving Rcpsp/Max With Durational Uncertainty, Na Fu, Hoong Chuin Lau, Pradeep Varakantham, Fei Xiao
Robust Local Search For Solving Rcpsp/Max With Durational Uncertainty, Na Fu, Hoong Chuin Lau, Pradeep Varakantham, Fei Xiao
Research Collection School Of Computing and Information Systems
Scheduling problems in manufacturing, logistics and project management have frequently been modeled using the framework of Resource Constrained Project Scheduling Problems with minimum and maximum time lags (RCPSP/max). Due to the importance of these problems, providing scalable solution schedules for RCPSP/max problems is a topic of extensive research. However, all existing methods for solving RCPSP/max assume that durations of activities are known with certainty, an assumption that does not hold in real world scheduling problems where unexpected external events such as manpower availability, weather changes, etc. lead to delays or advances in completion of activities. Thus, in this paper, our …
Robust Distributed Scheduling Via Time Period Aggregation, Shih-Fen Cheng, John Tajan, Hoong Chuin Lau
Robust Distributed Scheduling Via Time Period Aggregation, Shih-Fen Cheng, John Tajan, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
In this paper, we evaluate whether the robustness of a market mechanism that allocates complementary resources could be improved through the aggregation of time periods in which resources are consumed. In particular, we study a multi-round combinatorial auction that is built on a general equilibrium framework. We adopt the general equilibrium framework and the particular combinatorial auction design from the literature, and we investigate the benefits and the limitation of time-period aggregation when demand-side uncertainties are introduced. By using simulation experiments on a real-life resource allocation problem from a container port, we show that, under stochastic conditions, the performance variation …