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Articles 61 - 89 of 89
Full-Text Articles in Computer and Systems Architecture
Measuring And Modelling The Thermal Performance Of The Tamar Suspension Bridge Using A Wireless Sensor Network, Nicholas De Battista, James M. W. Brownjohn, Hwee-Pink Tan, Ki Young Koo
Measuring And Modelling The Thermal Performance Of The Tamar Suspension Bridge Using A Wireless Sensor Network, Nicholas De Battista, James M. W. Brownjohn, Hwee-Pink Tan, Ki Young Koo
Research Collection School Of Computing and Information Systems
A study on the thermal performance of the Tamar Suspension Bridge deck in Plymouth, UK, is presented in this paper. Ambient air, suspension cable, deck and truss temperatures were acquired using a wired sensor system. Deck extension data were acquired using a two-hop wireless sensor network. Empirical models relating the deck extension to various combinations of temperatures were derived and compared. The most accurate model, which used all the four temperature variables, predicted the deck extension with an accuracy of 99.4%. Time delays ranging from 10 to 66 min were identified between the daily cycles of the air temperature and …
Evaluating Electronic Market Designs: The Effects Of Competitive Arousal And Social Facilitation On Electronic Group Buying, Yuecheng Yu, Karl R. Lang, Alex Pelaez
Evaluating Electronic Market Designs: The Effects Of Competitive Arousal And Social Facilitation On Electronic Group Buying, Yuecheng Yu, Karl R. Lang, Alex Pelaez
Research Collection School Of Computing and Information Systems
This article presents an evaluation approach foralternative electronic market designs and examines theimpact of competitive arousal under time pressure onmarket performance in a group-buying setting. Drawingon theory from economics, decision theory, andinformation systems, we present a competitive arousalmodel for a social buying setting that posits thatintroducing competitive arousal among buyers reducesbuyer profits and that social facilitation can mitigate thesecosts through better task completion and time tocompletion rates. Using an economic experiment, wefound that rivalry has a negative effect on buyer profitsbut also that competitive arousal increases the efficiencyof social facilitation in terms of group formation. Wediscuss the implications of these …
Adaptive Computer‐Generated Forces For Simulator‐Based Training, Expert Systems With Applications, Teck-Hou Teng, Ah-Hwee Tan, Loo-Nin Teow
Adaptive Computer‐Generated Forces For Simulator‐Based Training, Expert Systems With Applications, Teck-Hou Teng, Ah-Hwee Tan, Loo-Nin Teow
Research Collection School Of Computing and Information Systems
Simulator-based training is in constant pursuit of increasing level of realism. The transition from doctrine-driven computer-generated forces (CGF) to adaptive CGF represents one such effort. The use of doctrine-driven CGF is fraught with challenges such as modeling of complex expert knowledge and adapting to the trainees’ progress in real time. Therefore, this paper reports on how the use of adaptive CGF can overcome these challenges. Using a self-organizing neural network to implement the adaptive CGF, air combat maneuvering strategies are learned incrementally and generalized in real time. The state space and action space are extracted from the same hierarchical doctrine …
An Experimental Study For Inter-User Interference Mitigation In Wireless Body Sensor Networks, Bin Cao, Yu Ge, Chee Wee Kim, Gang Feng, Hwee-Pink Tan, Yun Li
An Experimental Study For Inter-User Interference Mitigation In Wireless Body Sensor Networks, Bin Cao, Yu Ge, Chee Wee Kim, Gang Feng, Hwee-Pink Tan, Yun Li
Research Collection School Of Computing and Information Systems
Inter-user interference degrades the reliability of data delivery in wireless body sensor networks (WBSNs) in dense deployments when multiple users wearing WBSNs are in close proximity to one another. The impact of such interference in realistic WBSN systems is significant but is not well explored. To this end, we investigate and analyze the impact of inter-user interference on packet delivery ratio (PDR) and throughput. We conduct extensive experiments based on the TelosB WBSN platform, considering unslotted carrier sense multiple access (CSMA) with collision avoidance (CA) and slotted CSMA/CA modes in IEEE 802.15.4 MAC, respectively. In order to mitigate interuser interference, …
Clustering Algorithms For Maximizing The Lifetime Of Wireless Sensor Networks With Energy-Harvesting Sensors, Pengfei Zhang, Gaoxi Xiao, Hwee-Pink Tan
Clustering Algorithms For Maximizing The Lifetime Of Wireless Sensor Networks With Energy-Harvesting Sensors, Pengfei Zhang, Gaoxi Xiao, Hwee-Pink Tan
Research Collection School Of Computing and Information Systems
Motivated by recent developments in wireless sensor networks (WSNs), we present several efficient clustering algorithms for maximizing the lifetime of WSNs, i.e., the duration till a certain percentage of the nodes die. Specifically, an optimization algorithm is proposed for maximizing the lifetime of a single-cluster network, followed by an extension to handle multi-cluster networks. Then we study the joint problem of prolonging network lifetime by introducing energy-harvesting (EH) nodes. An algorithm is proposed for maximizing the network lifetime where EH nodes serve as dedicated relay nodes for cluster heads (CHs). Theoretical analysis and extensive simulation results show that the proposed …
Energy-Neutral Scheduling And Forwarding In Environmentally-Powered Wireless Sensor Networks, Alvin Cerdena Valera, Weng Seng Soh, Hwee-Pink Tan
Energy-Neutral Scheduling And Forwarding In Environmentally-Powered Wireless Sensor Networks, Alvin Cerdena Valera, Weng Seng Soh, Hwee-Pink Tan
Research Collection School Of Computing and Information Systems
In environmentally-powered wireless sensor networks (EPWSNs), low latency wakeup scheduling and packet forwarding is challenging due to dynamic duty cycling, posing time-varying sleep latencies and necessitating the use of dynamic wakeup schedules. We show that the variance of the intervals between receiving wakeup slots affects the expected sleep latency: when the variance of the intervals is low (high), the expected latency is low (high). We therefore propose a novel scheduling scheme that uses the bit-reversal permutation sequence (BRPS) – a finite integer sequence that positions receiving wakeup slots as evenly as possible to reduce the expected sleep latency. At the …
Cognitive Architectures And Autonomy: Commentary And Response, Włodzisław Duch, Ah-Hwee Tan, Stan Franklin
Cognitive Architectures And Autonomy: Commentary And Response, Włodzisław Duch, Ah-Hwee Tan, Stan Franklin
Research Collection School Of Computing and Information Systems
This paper provides a very useful and promising analysis and comparison of current architectures of autonomous intelligent systems acting in real time and specific contexts, with all their constraints. The chosen issue of Cognitive Architectures and Autonomy is really a challenge for AI current projects and future research. I appreciate and endorse not only that challenge but many specific choices and claims; in particular: (i) that “autonomy” is a key concept for general intelligent systems; (ii) that “a core issue in cognitive architecture is the integration of cognitive processes ....”; (iii) the analysis of features and capabilities missing in current …
Sensor Openflow: Enabling Software-Defined Wireless Sensor Networks, Tie Luo, Hwee-Pink Tan, Tony Q. S. Quek
Sensor Openflow: Enabling Software-Defined Wireless Sensor Networks, Tie Luo, Hwee-Pink Tan, Tony Q. S. Quek
Research Collection School Of Computing and Information Systems
While it has been a belief for over a decade that wireless sensor networks (WSN) are application-specific, we argue that it can lead to resource underutilization and counter-productivity. We also identify two other main problems with WSN: rigidity to policy changes and difficulty to manage. In this paper, we take a radical, yet backward and peer compatible, approach to tackle these problems inherent to WSN. We propose a Software-Defined WSN architecture and address key technical challenges for its core component, Sensor OpenFlow. This work represents the first effort that synergizes software-defined networking and WSN.
Ifalcon: A Neural Architecture For Hierarchical Planning, Budhitama Subagdja, Ah-Hwee Tan
Ifalcon: A Neural Architecture For Hierarchical Planning, Budhitama Subagdja, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
Hierarchical planning is an approach of planning by composing and executing hierarchically arranged predefined plans on the fly to solve some problems. This approach commonly relies on a domain expert providing all semantic and structural knowledge. One challenge is how the system deals with incomplete ill-defined knowledge while the solution can be achieved on the fly. Most symbolic-based hierarchical planners have been devised to allow the knowledge to be described expressively. However, in some cases, it is still difficult to produce the appropriate knowledge due to the complexity of the problem domain especially if the missing knowledge must be acquired …
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 …
Simultaneous Camera Pose And Correspondence Estimation With Motion Coherence, Wen-Yan Lin, Loong-Fah Cheong, Ping Tan, Guo Dong, Siying Liu
Simultaneous Camera Pose And Correspondence Estimation With Motion Coherence, Wen-Yan Lin, Loong-Fah Cheong, Ping Tan, Guo Dong, Siying Liu
Research Collection School Of Computing and Information Systems
Traditionally, the camera pose recovery problem has been formulated as one of estimating the optimal camera pose given a set of point correspondences. This critically depends on the accuracy of the point correspondences and would have problems in dealing with ambiguous features such as edge contours and high visual clutter. Joint estimation of camera pose and correspondence attempts to improve performance by explicitly acknowledging the chicken and egg nature of the pose and correspondence problem. However, such joint approaches for the two-view problem are still few and even then, they face problems when scenes contain largely edge cues with few …
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 …
Using Service Responsibility Tables To Supplement Uml In Analyzing E-Service Systems, Xin Tan, Steven Alter, Keng Siau
Using Service Responsibility Tables To Supplement Uml In Analyzing E-Service Systems, Xin Tan, Steven Alter, Keng Siau
Research Collection School Of Computing and Information Systems
This paper proposes using Service Responsibility Tables (SRTs) as a tool in analyzing e-service systems. First it discusses difficulties and deficiencies of using formal modeling languages such as UML in analyzing e-service systems. It proposes using SRTs as an informal language and lightweight analytical tool to be used by business professionals in analyzing e-service systems. SRTs are based on a service value chain framework but do not rely on abstract concepts and constructs, and therefore can be used by business professionals to supplement UML. We suggest a set of heuristics for transforming SRTs into two key UML diagrams, thereby illustrating …
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 …
Wireless Sensing Without Sensors: An Experimental Study Of Motion/Intrusion Detection Using Rf Irregularity, Wei Qi Lee, Winston K. G. Seah, Hwee-Pink Tan, Zexi Yao
Wireless Sensing Without Sensors: An Experimental Study Of Motion/Intrusion Detection Using Rf Irregularity, Wei Qi Lee, Winston K. G. Seah, Hwee-Pink Tan, Zexi Yao
Research Collection School Of Computing and Information Systems
Motion and intrusion detection are often cited as wireless sensor network (WSN) applications with typical configurations comprising clusters of wireless nodes equipped with motion sensors to detect human motion. Currently, WSN performance is subjected to several constraints, namely radio irregularity and finite on-board computation/energy resources. Radio irregularity in radio frequency (RF) propagation rises to a higher level in the presence of human activity due to the absorption effect of the human body. In this paper, we investigate the feasibility of monitoring RF transmission for the purpose of intrusion detection through experimentation. With empirical data obtained from the Crossbow TelosB platform …
A Self-Organizing Neural Architecture Integrating Desire, Intention And Reinforcement Learning, Ah-Hwee Tan, Yu-Hong Feng, Yew-Soon Ong
A Self-Organizing Neural Architecture Integrating Desire, Intention And Reinforcement Learning, Ah-Hwee Tan, Yu-Hong Feng, Yew-Soon Ong
Research Collection School Of Computing and Information Systems
This paper presents a self-organizing neural architecture that integrates the features of belief, desire, and intention (BDI) systems with reinforcement learning. Based on fusion Adaptive Resonance Theory (fusion ART), the proposed architecture provides a unified treatment for both intentional and reactive cognitive functionalities. Operating with a sense-act-learn paradigm, the low level reactive module is a fusion ART network that learns action and value policies across the sensory, motor, and feedback channels. During performance, the actions executed by the reactive module are tracked by a high level intention module (also a fusion ART network) that learns to associate sequences of actions …
When Discrete Meets Differential: Assessing The Stability Of Structure From Small Motion, Wen-Yan Lin, Geok-Choo Tan, Loong-Fah Cheong
When Discrete Meets Differential: Assessing The Stability Of Structure From Small Motion, Wen-Yan Lin, Geok-Choo Tan, Loong-Fah Cheong
Research Collection School Of Computing and Information Systems
We provide a theoretical proof showing that under a proportional noise model, the discrete eight point algorithm behaves similarly to the differential eight point algorithm when the motion is small. This implies that the discrete algorithm can handle arbitrarily small motion for a general scene, as long as the noise decreases proportionally with the amount of image motion and the proportionality constant is small enough. This stability result extends to all normalized variants of the eight point algorithm. Using simulations, we show that given arbitrarily small motions and proportional noise regime, the normalized eight point algorithms outperform their differential counterparts …
Crctol: A Semantic Based Domain Ontology Learning System, Xing Jiang, Ah-Hwee Tan
Crctol: A Semantic Based Domain Ontology Learning System, Xing Jiang, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
Domain ontologies play an important role in supporting knowledge‐based applications in the Semantic Web. To facilitate the building of ontologies, text mining techniques have been used to perform ontology learning from texts. However, traditional systems employ shallow natural language processing techniques and focus only on concept and taxonomic relation extraction. In this paper we present a system, known as Concept‐Relation‐Concept Tuple‐based Ontology Learning (CRCTOL), for mining ontologies automatically from domain‐specific documents. Specifically, CRCTOL adopts a full text parsing technique and employs a combination of statistical and lexico‐syntactic methods, including a statistical algorithm that extracts key concepts from a document collection, …
Analysis Of Tradeoffs Between Buffer And Qos Requirements In Wireless Networks, Raphael Rom, Hwee-Pink Tan
Analysis Of Tradeoffs Between Buffer And Qos Requirements In Wireless Networks, Raphael Rom, Hwee-Pink Tan
Research Collection School Of Computing and Information Systems
In this paper, we consider the scheduling problem where data packets from K input-flows need to be delivered to K corresponding wireless receivers over a heterogeneous wireless channel. Our objective is to design a wireless scheduler that achieves good throughput and fairness performance while minimizing the buffer requirement at each wireless receiver. This is a challenging problem due to the unique characteristics of the wireless channel. We propose a novel idea of exploiting both the long-term and short-term error behavior of the wireless channel in the scheduler design. In addition to typical first-order Quality of Service (QoS) metrics such as …
Admission Control For Differentiated Services In Future Generation Cdma Networks, Hwee-Pink Tan, Rudesindo Núñez-Queija, Adriana F. Gabor, Onno J. Boxma
Admission Control For Differentiated Services In Future Generation Cdma Networks, Hwee-Pink Tan, Rudesindo Núñez-Queija, Adriana F. Gabor, Onno J. Boxma
Research Collection School Of Computing and Information Systems
Future Generation CDMA wireless systems, e.g., 3G, can simultaneously accommodate flow transmissions of users with widely heterogeneous applications. As radio resources are limited, we propose an admission control rule that protects users with stringent transmission bit-rate requirements (“streaming traffic”) while offering sufficient capacity over longer time intervals to delay-tolerant users (“elastic traffic”). While our strategy may not satisfy classical notions of fairness, we aim to reduce congestion and increase overall throughput of elastic users. Using time-scale decomposition, we develop approximations to evaluate the performance of our differentiated admission control strategy to support integrated services with transmission bit-rate requirements in a …
Integrated Cognitive Architectures: A Survey, Hui-Qing Chong, Ah-Hwee Tan, Gee-Wah Ng
Integrated Cognitive Architectures: A Survey, Hui-Qing Chong, Ah-Hwee Tan, Gee-Wah Ng
Research Collection School Of Computing and Information Systems
This article aims to present an account of the state of the art research in the field of integrated cognitive architectures by providing a review of six cognitive architectures, namely Soar, ACT-R, ICARUS, BDI, the subsumption architecture and CLARION. We conduct a detailed functional comparison by looking at a wide range of cognitive components, including perception, memory, goal representation, planning, problem solving, reasoning, learning, and relevance to neurobiology. In addition, we study the range of benchmarks and applications that these architectures have been applied to. Although no single cognitive architecture has provided a full solution with the level of human …
Modelling Situation Awareness For Context‐Aware Decision Support, Yu-Hong Feng, Teck-Hou Teng, Ah-Hwee Tan
Modelling Situation Awareness For Context‐Aware Decision Support, Yu-Hong Feng, Teck-Hou Teng, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
Situation awareness modelling is popularly used in the command and control domain for situation assessment and decision support. However, situation models in real-world applications are typically complex and not easy to use. This paper presents a Context-aware Decision Support (CaDS) system, which consists of a situation model for shared situation awareness modelling and a group of entity agents, one for each individual user, for focused and customized decision support. By incorporating a rule-based inference engine, the entity agents provide functions including event classification, action recommendation, and proactive decision making. The implementation and the performance of the proposed system are demonstrated …
Self-Organizing Neural Architectures And Cooperative Learning In A Multiagent Environment, Dan Xiao, Ah-Hwee Tan
Self-Organizing Neural Architectures And Cooperative Learning In A Multiagent Environment, Dan Xiao, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
Temporal-Difference–Fusion Architecture for Learning, Cognition, and Navigation (TD-FALCON) is a generalization of adaptive resonance theory (a class of self-organizing neural networks) that incorporates TD methods for real-time reinforcement learning. In this paper, we investigate how a team of TD-FALCON networks may cooperate to learn and function in a dynamic multiagent environment based on minefield navigation and a predator/prey pursuit tasks. Experiments on the navigation task demonstrate that TD-FALCON agent teams are able to adapt and function well in a multiagent environment without an explicit mechanism of collaboration. In comparison, traditional Q-learning agents using gradient-descent-based feedforward neural networks, trained with the …
A Two-Phase Approach To Interactivity Enhancement For Large-Scale Distributed Virtual Environments, Nguyen Binh Duong Ta, Suiping Zhou
A Two-Phase Approach To Interactivity Enhancement For Large-Scale Distributed Virtual Environments, Nguyen Binh Duong Ta, Suiping Zhou
Research Collection School Of Computing and Information Systems
Distributed virtual environments (DVEs) are distributed systems that allow multiple geographically distributed clients (users) to interact simultaneously in a computer-generated, shared virtual world. Applications of DVEs can be seen in many areas nowadays, such as online games, military simulations, collaborative designs, etc. To support large-scale DVEs with real-time interactions among thousands or even more distributed clients, a geographically distributed server architecture (GDSA) is generally needed, and the virtual world can be partitioned into many distinct zones to distribute the load among the servers. Due to the geographic distributions of clients and servers in such architectures, it is essential to efficiently …
Parameter Inference Of Queueing Models For It Systems Using End-To-End Measurements, Laura Wynter, Cathy H. Xia, Fan Zhang
Parameter Inference Of Queueing Models For It Systems Using End-To-End Measurements, Laura Wynter, Cathy H. Xia, Fan Zhang
Research Collection School Of Computing and Information Systems
As Information Technology (IT) matures and expands in the scope of available applications, IT systems increase at a fascinating rate in both size and complexity. For example, today, a typical Web service hosting center may have hundreds of nodes and dozens of different applications simultaneously running on it. Each of the nodes in turn has often multiple processors and layered caches. These nodes make use of both local and shared storage systems. The size and complexity of such systems make performance modeling much more difficult, if at all tractable. Detailed modeling, fine tuning and accurate analysis can be carried out …
Optimal Location Of Intermodal Freight Hubs, Illia Racunica, Laura Wynter
Optimal Location Of Intermodal Freight Hubs, Illia Racunica, Laura Wynter
Research Collection School Of Computing and Information Systems
We present an optimization model that has been developed to address the problem of increasing the share of rail in intermodal transport through the use of hub-and-spoke type networks for freight rail. The model defined is a generalization of the hub location problem in that it allows for non-linear and concave cost functions on different segments. A linearization procedure along with two efficient variable-reduction heuristics was developed for its resolution, making use of recent results on polyhedral properties of this class of problems. Computational experience and a qualitative analysis from a case study on the Alpine freight network is provided.
Critical Factors For Successful Implementation Of Enterprise Systems, Fiona Fui-Hoon Nah, J. Lau, J. Kuang
Critical Factors For Successful Implementation Of Enterprise Systems, Fiona Fui-Hoon Nah, J. Lau, J. Kuang
Research Collection School Of Computing and Information Systems
Enterprise resource planning (ERP) systems have emerged as the core of successful information management and the enterprise backbone of organizations. The difficulties of ERP implementations have been widely cited in the literature but research on the critical factors for initial and ongoing ERP implementation success is rare and fragmented. Through a comprehensive review of the literature, 11 factors were found to be critical to ERP implementation success – ERP teamwork and composition; change management program and culture; top management support; business plan and vision; business process reengineering with minimum customization; project management; monitoring and evaluation of performance; effective communication; software …
Supervised Adaptive Resonance Theory And Rules, Ah-Hwee Tan
Supervised Adaptive Resonance Theory And Rules, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
Supervised Adaptive Resonance Theory is a family of neural networks that performs incremental supervised learning of recognition categories (pattern classes) and multidimensional maps of both binary and analog patterns. This chapter highlights that the supervised ART architecture is compatible with IF-THEN rule-based symbolic representation. Specifically, the knowledge learned by a supervised ART system can be readily translated into rules for interpretation. Similarly, a priori domain knowledge in the form of IF-THEN rules can be converted into a supervised ART architecture. Not only does initializing networks with prior knowledge improve predictive accuracy and learning efficiency, the inserted symbolic knowledge can also …