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Articles 751 - 780 of 836
Full-Text Articles in Engineering
Winning Back The Cup For Distributed Pomdps: Planning Over Continuous Belief Spaces, Pradeep Varakantham, Ranjit Nair, Milind Tambe, Makoto Yokoo
Winning Back The Cup For Distributed Pomdps: Planning Over Continuous Belief Spaces, Pradeep Varakantham, Ranjit Nair, Milind Tambe, Makoto Yokoo
Research Collection School Of Computing and Information Systems
Distributed Partially Observable Markov Decision Problems (Distributed POMDPs) are evolving as a popular approach for modeling multiagent systems, and many different algorithms have been proposed to obtain locally or globally optimal policies. Unfortunately, most of these algorithms have either been explicitly designed or experimentally evaluated assuming knowledge of a starting belief point, an assumption that often does not hold in complex, uncertain domains. Instead, in such domains, it is important for agents to explicitly plan over continuous belief spaces. This paper provides a novel algorithm to explicitly compute finite horizon policies over continuous belief spaces, without restricting the space of …
Evaluation Of Time-Varying Availability In Multi-Echelon Spare Parts Systems With Passivation, Hoong Chuin Lau, Huawei Song, Chuen Teck See, Siew Yen Cheng
Evaluation Of Time-Varying Availability In Multi-Echelon Spare Parts Systems With Passivation, Hoong Chuin Lau, Huawei Song, Chuen Teck See, Siew Yen Cheng
Research Collection School Of Computing and Information Systems
The popular models for repairable item inventory, both in the literature as well as practical applications, assume that the demands for items are independent of the number of working systems. However this assumption can introduce a serious underestimation of availability when the number of working systems is small, the failure rate is high or the repair time is long. In this paper, we study a multi-echelon repairable item inventory system under the phenomenon of passivation, i.e. serviceable items are passivated (“switched off”) upon system failure. This work is motivated by corrective maintenance of high-cost technical equipment in the miltary. We …
Splash: Systematic Proteomics Laboratory Analysis And Storage Hub, Siaw Ling Lo, You Tao, Qingsong Lin, Shashikant B. Joshi, Maxey Chung, Choy Leong Hew
Splash: Systematic Proteomics Laboratory Analysis And Storage Hub, Siaw Ling Lo, You Tao, Qingsong Lin, Shashikant B. Joshi, Maxey Chung, Choy Leong Hew
Research Collection School Of Computing and Information Systems
In the field of proteomics, the increasing difficulty to unify the data format, due to the different platforms/instrumentation and laboratory documentation systems, greatly hinders experimental data verification, exchange, and comparison. Therefore, it is essential to establish standard formats for every necessary aspect of proteomics data. One of the recently published data models is the proteomics experiment data repository [Taylor, C. F., Paton, N. W., Garwood, K. L., Kirby, P. D. et al., Nat. Biotechnol. 2003, 21, 247-254]. Compliant with this format, we developed the systematic proteomics laboratory analysis and storage hub (SPLASH) database system as an informatics infrastructure to support …
Threading And Autodocumenting News Videos: A Promising Solution To Rapidly Browse News Topics, Xiao Wu, Chong-Wah Ngo, Qing Li
Threading And Autodocumenting News Videos: A Promising Solution To Rapidly Browse News Topics, Xiao Wu, Chong-Wah Ngo, Qing Li
Research Collection School Of Computing and Information Systems
This paper describes the techniques in threading and autodocumenting news stories according to topic themes. Initially, we perform story clustering by exploiting the duality between stories and textual-visual concepts through a co-clustering algorithm. The dependency among stories of a topic is tracked by exploring the textual-visual novelty and redundancy of stories. A novel topic structure that chains the dependencies of stories is then presented to facilitate the fast navigation of the news topic. By pruning the peripheral and redundant news stories in the topic structure, a main thread is extracted for autodocumentary
Multiagent Teamwork: Hybrid Approaches, Praveen Paruchuri, Emma Bowring, Ranjit Nair, Jonathan Pearce, Nathan Schurr, Milind Tambe, Pradeep Varakantham
Multiagent Teamwork: Hybrid Approaches, Praveen Paruchuri, Emma Bowring, Ranjit Nair, Jonathan Pearce, Nathan Schurr, Milind Tambe, Pradeep Varakantham
Research Collection School Of Computing and Information Systems
Today within the multiagent community, we see at least four competing methods to building multiagent systems: beliefdesireintention (BDI), distributed constraint optimization (DCOP), distributed POMDPs, and auctions or game-theoretic methods. While there is exciting progress within each approach, there is a lack of cross-cutting research. This article highlights the various hybrid techniques for multiagent teamwork developed by the teamcore group. In particular, for the past decade, the TEAMCORE research group has focused on building agent teams in complex, dynamic domains. While our early work was inspired by BDI, we will present an overview of recent research that uses DCOPs and distributed …
Visualization For Analyzing Trajectory-Based Metaheuristic Search Algorithms, Steven Halim, Roland H. C. Yap, Hoong Chuin Lau
Visualization For Analyzing Trajectory-Based Metaheuristic Search Algorithms, Steven Halim, Roland H. C. Yap, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
No abstract provided.
A Generic Object-Oriented Tabu Search Framework, Hoong Chuin Lau, Xiaomin Jia, Wee Chong Wan
A Generic Object-Oriented Tabu Search Framework, Hoong Chuin Lau, Xiaomin Jia, Wee Chong Wan
Research Collection School Of Computing and Information Systems
Presently, most tabu search designers devise their applications without considering the potential of design and code reuse, which consequently prolong the development of subsequent applications. In this paper, we propose a software solution known as Tabu Search Framework (TSF), which is a generic C++ software framework for tabu search implementation. The framework excels in code recycling through the use of a well- designed set of generic abstract classes that clearly define their collaborative roles in the algorithm. Additionally, the framework incorporates a centralized process and control mechanism that enhances the search with intelligence. This results in a generic framework that …
Solving Generalized Open Constraint Optimization Problem Using Two-Level Multi-Agent Framework, Hoong Chuin Lau, Lei Zhang, Chang Liu
Solving Generalized Open Constraint Optimization Problem Using Two-Level Multi-Agent Framework, Hoong Chuin Lau, Lei Zhang, Chang Liu
Research Collection School Of Computing and Information Systems
The Open Constraint Optimization Problem (OCOP) refers to the COP where constraints and variable domains can change over time and agents' opinions have to be sought over a distributed network to form a solution. The openness of the problem has caused conventional approaches to COP such as branch-and-bound to fail to find optimal solutions. OCOP is a new problem and the approach to find an optimal solution (minimum total cost) introduced in [1] is based on an unrealistic assumption that agents are willing to report their options in nondecreasing order of cost. In this paper, we study a generalized OCOP …
Partial Adjustable Autonomy In Multi-Agent Environment And Its Application To Military Logistics, Hoong Chuin Lau, Lucas Agussurja, Ramesh Thangarajoo
Partial Adjustable Autonomy In Multi-Agent Environment And Its Application To Military Logistics, Hoong Chuin Lau, Lucas Agussurja, Ramesh Thangarajoo
Research Collection School Of Computing and Information Systems
In a rapidly changing environment, the behavior and decision-making power of agents may have to be adaptive with respect to a fluctuating autonomy. In this paper, a centralized fuzzy approach is proposed to sense changes in environmental conditions and translate them to changes in agent autonomy. A distributed coalition formation scheme is then applied to allow agents in the new autonomy to renegotiate to establish schedule consistency. The proposed framework is applied to a real-time logistics control of a military hazardous material storage facility under peace-to-war transition.
Evaluation Of Time-Varying Availability In Multi-Echelon Inventory System With Combat Damage, Hoong Chuin Lau, Huawei Song
Evaluation Of Time-Varying Availability In Multi-Echelon Inventory System With Combat Damage, Hoong Chuin Lau, Huawei Song
Research Collection School Of Computing and Information Systems
The models for multi-echelon inventory systems in existing literatures predominantly address failures due to reliability in peacetime. In wartime or even peacetime operational scenarios, unexpected combat damage can cause a large number of systems to be heavily damaged, to the extent that they become irreparable. In this paper, we study a multi-echelon spare parts support system under combat damage, discuss the replenishment policy and propose an approximate method to evaluate the time-varying system performance operational availability considering the effect of passivation. Experiments show our model works well and efficiently against simulation.
Tuning Tabu Search Strategies Via Visual Diagnosis, Steven Halim, Wee Chong Wan, Hoong Chuin Lau
Tuning Tabu Search Strategies Via Visual Diagnosis, Steven Halim, Wee Chong Wan, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
While designing working metaheuristics can be straightforward, tuning them to solve the underlying combinatorial optimization problem well can be tricky. Several tuning methods have been proposed but they do not address the new aspect of our proposed classification of the metaheuristic tuning problem: tuning search strategies. We propose a tuning methodology based on Visual Diagnosis and a generic tool called Visualizer for Metaheuristics Development Framework(V-MDF) to address specifically the problem of tuning search (particularly Tabu Search) strategies. Under V-MDF, we propose the use of a Distance Radar visualizer where the human and computer can collaborate to diagnose the occurrence of …
Dispatching Vehicles In A Mega Container Terminal, Ebru K. Bish, Frank Y. Chen, Thin Yin Leong, Barry L. Nelson, Jonathan W. C. Ng, David Simchi-Levi
Dispatching Vehicles In A Mega Container Terminal, Ebru K. Bish, Frank Y. Chen, Thin Yin Leong, Barry L. Nelson, Jonathan W. C. Ng, David Simchi-Levi
Research Collection School Of Computing and Information Systems
We consider a container terminal discharging and uploading containers to and from ships. The discharged containers are stored at prespecified storage locations in the terminal yard. Containers are moved between the ship area and the yard using a fleet of vehicles, each of which can carry one container at a time. The problem is to dispatch vehicles to the containers so as to minimize the total time it takes to serve a ship, which is the total time it takes to discharge all containers from the ship and upload new containers onto the ship. We develop easily implementable heuristic algorithms …
Exploiting Belief Bounds: Practical Pomdps For Personal Assistant Agents, Pradeep Varakantham, Rajiv Maheswaran, Milind Tambe
Exploiting Belief Bounds: Practical Pomdps For Personal Assistant Agents, Pradeep Varakantham, Rajiv Maheswaran, Milind Tambe
Research Collection School Of Computing and Information Systems
Agents or agent teams deployed to assist humans often face the challenges of monitoring the state of key processes in their environment (including the state of their human users themselves) and making periodic decisions based on such monitoring. POMDPs appear well suited to enable agents to address these challenges, given the uncertain environment and cost of actions, but optimal policy generation for POMDPs is computationally expensive. This paper introduces three key techniques to speedup POMDP policy generation that exploit the notion of progress or dynamics in personal assistant domains. Policy computation is restricted to the belief space polytope that remains …
Approximate Strategic Reasoning Through Hierarchical Reduction Of Large Symmetric Games, Michael P. Wellman, Daniel M. Reeves, Kevin M. Lochner, Shih-Fen Cheng, Rahul Suri
Approximate Strategic Reasoning Through Hierarchical Reduction Of Large Symmetric Games, Michael P. Wellman, Daniel M. Reeves, Kevin M. Lochner, Shih-Fen Cheng, Rahul Suri
Research Collection School Of Computing and Information Systems
To deal with exponential growth in the size of a game with the number of agents, we propose an approximation based on a hierarchy of reduced games. The reduced game achieves savings by restricting the number of agents playing any strategy to fixed multiples. We validate the idea through experiments on randomly generated local-effect games. An extended application to strategic reasoning about a complex trading scenario motivates the approach, and demonstrates methods for game-theoretic reasoning over incompletely-specified games at multiple levels of granularity.
Effect Of Training Datasets On Support Vector Machine Prediction Of Protein-Protein Interactions, Siaw Ling Lo, Cong Zhong Cai, Maxey Chung, Yu Zong Chen
Effect Of Training Datasets On Support Vector Machine Prediction Of Protein-Protein Interactions, Siaw Ling Lo, Cong Zhong Cai, Maxey Chung, Yu Zong Chen
Research Collection School Of Computing and Information Systems
Knowledge of protein-protein interaction is useful for elucidating protein function via the concept of 'guilt-by-association'. A statistical learning method, Support Vector Machine (SVM), has recently been explored for the prediction of protein-protein interactions using artificial shuffled sequences as hypothetical noninteracting proteins and it has shown promising results (Bock, J. R., Gough, D. A., Bioinformatics 2001, 17, 455-460). It remains unclear however, how the prediction accuracy is affected if real protein sequences are used to represent noninteracting proteins. In this work, this effect is assessed by comparison of the results derived from the use of real protein sequences with that derived …
A Multi-Agent Approach For Solving Optimization Problems Involving Expensive Resources, Hoong Chuin Lau, H. Wang
A Multi-Agent Approach For Solving Optimization Problems Involving Expensive Resources, Hoong Chuin Lau, H. Wang
Research Collection School Of Computing and Information Systems
In this paper, we propose a multi-agent approach for solving a class of optimization problems involving expensive resources, where monolithic local search schemes perform miserably. More specifically, we study the class of bin-packing problems. Under our proposed Fine-Grained Agent System scheme, rational agents work both collaboratively and selfishly based on local search and mimic physics-motivated systems. We apply our approach to a generalization of bin-packing - the Inventory Routing Problem with Time Windows - which is an important logistics problem, and demonstrate the efficiency and effectiveness of our approach.
Robust Temporal Constraint Networks, Hoong Chuin Lau, Thomas Ou, Melvyn Sim
Robust Temporal Constraint Networks, Hoong Chuin Lau, Thomas Ou, Melvyn Sim
Research Collection School Of Computing and Information Systems
In this paper, we propose the Robust Temporal Constraint Network (RTCN) model for simple temporal constraint networks where activity durations are bounded by random variables. The problem is to determine whether such temporal network can be executed with failure probability less than a given 0 ≤ E ≤ 1 for each possible instantiation of the random variables, and if so. how one might find a feasible schedule with each given instantiation. The advantage of our model is that one can vary the value of ∊ to control the level of conservativeness of the solution. We present a computationally tractable and …
Corrective Maintenance Optimization In An Air Force, Hoong Chuin Lau, K. Y. Neo, W. C. Wan
Corrective Maintenance Optimization In An Air Force, Hoong Chuin Lau, K. Y. Neo, W. C. Wan
Research Collection School Of Computing and Information Systems
Successful military mission planning and execution depend critically on equipment serviceability and resupply. Due to the stochastic nature of demands, the forecast of optimal spares and resources needed to guarantee the level of serviceability is a complex problem, especially in a multi-echelon setting. In this paper, we propose a decision-support concept and software tool known as Corrective Maintenance Optimizer (CMO) that helps to optimize system availability, through proper allocation of spare parts, both strategically and operationally.
Two-Echelon Repairable Item Inventory System With Limited Repair Capacity Under Nonstationary Demands, Hoong Chuin Lau, Huawei Song
Two-Echelon Repairable Item Inventory System With Limited Repair Capacity Under Nonstationary Demands, Hoong Chuin Lau, Huawei Song
Research Collection School Of Computing and Information Systems
We study a repairable item inventory system under limited repair capacity and nonstationary Poisson demands, motivated by corrective maintenance of military equipment. Our goal is to minimize the cost of both spare and repair resource allocation. We propose an efficient analytical model that combines optimization modeling and queuing theory.
Job Scheduling With Unfixed Availability Constraints, Hoong Chuin Lau, C. Zhang
Job Scheduling With Unfixed Availability Constraints, Hoong Chuin Lau, C. Zhang
Research Collection School Of Computing and Information Systems
Standard scheduling theory assumes that all machines are continuously available throughout the planning horizon. In many manufacturing and service management situations however, machines need to be maintained periodically to prevent malfunctions. During the maintenance period, a machine is not available for processing jobs. Hence, a more realistic scheduling model should take into account machine maintenance activities. In this paper, we study the problem of job scheduling with unfixed availability constraints on a single machine. We first propose a preliminary classification for the scheduling problem with unfixed availability constraints based on maintenance constraints, job characteristics and objective function. We divide our …
Logistics Network Design With Differentiated Delivery Lead Time: A Chemical Industry Case Study, Michelle Lee Fong Cheong, Rohit Bhatnagar, Stephen C. Graves
Logistics Network Design With Differentiated Delivery Lead Time: A Chemical Industry Case Study, Michelle Lee Fong Cheong, Rohit Bhatnagar, Stephen C. Graves
Research Collection School Of Computing and Information Systems
Most logistics network design models assume exogenous customer demand that is independent of the service time or level. This paper examines the benefits of segmenting demand according to lead-time sensitivity of customers. To capture lead-time sensitivity in the network design model, we use a facility grouping method to ensure that the different demand classes are satisfied on time. In addition, we perform a series of computational experiments to develop a set of managerial insights for the network design decision making process.
A Periodic-Review Inventory Model With Application To The Continuous-Review Obsolescence Problem, Yuyue Song, Hoong Chuin Lau
A Periodic-Review Inventory Model With Application To The Continuous-Review Obsolescence Problem, Yuyue Song, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
In this paper we consider a stochastic-demand periodic-review inventory model with sudden obsolescence. We characterize the structure of the optimal policy and propose a dynamic programming algorithm for computing its parameters. We then utilize this algorithm to approximate the solution to the continuous-review sudden obsolescence problem with general obsolescence distribution. We prove convergence of our approximation scheme, and demonstrate it numerically against known closed-form solutions of special cases.
A Development Framework For Rapid Metaheuristics Hybridization, Hoong Chuin Lau, M. K. Lim, W. C. Wan, S. Halim
A Development Framework For Rapid Metaheuristics Hybridization, Hoong Chuin Lau, M. K. Lim, W. C. Wan, S. Halim
Research Collection School Of Computing and Information Systems
While meta-heuristics are effective for solving large-scale combinatorial optimization problems, they result from time-consuming trial-and-error algorithm design tailored to specific problems. For this reason, a software tool for rapid prototyping of algorithms would save considerable resources. This work presents a generic software framework that reduces development time through abstract classes and software reuse, and more importantly, aids design with support of user-defined strategies and hybridization of meta-heuristics. Most interestingly, we propose a novel way of redefining hybridization with the use of the "request and response" metaphor, which form an abstract concept for hybridization. Different hybridization schemes can now be formed …
A Two-Level Framework For Coalition Formation Via Optimization And Agent Negotiation, Hoong Chuin Lau, Lei Zhang
A Two-Level Framework For Coalition Formation Via Optimization And Agent Negotiation, Hoong Chuin Lau, Lei Zhang
Research Collection School Of Computing and Information Systems
We present a two-level coalition formation approach based on a centralized optimization model on the upper level, and a distributed agent-negotiation model on the lower level. This approach allows us to balance agent self-interests against a high joint utility. Experimental results show that the two-level coalition formation mechanism will increase not only the overall utility of the coalition, but also the individual utility of most participating agents. The results also suggest it is better for the agents to be partially cooperative rather than either fully cooperative or self-interested in our setting.
Transport Logistics Planning With Service-Level Constraints, Hoong Chuin Lau, K. M. Ng, Xintao Wu
Transport Logistics Planning With Service-Level Constraints, Hoong Chuin Lau, K. M. Ng, Xintao Wu
Research Collection School Of Computing and Information Systems
In this paper, we study a logistics problem arising in military transport planning. A military organization operates a large fleet of vehicles in a depot to serve the requests of various operational units. Each request has a fixed start and end time, and is served by a prescribed number of vehicles. We address the following two problems: (1) how many vehicles are at least needed to meet a given service level of requests; and (2) suppose we allow each request to shift its start time by a constant duration, call all the requests be met? A Niche genetic algorithm, together …
Taking Dcop To The Real World: Efficient Complete Solutions For Distributed Event Scheduling, Rajiv Maheswaran, Milind Tambe, Emma Bowring, Jonathan Pearce, Pradeep Varakantham
Taking Dcop To The Real World: Efficient Complete Solutions For Distributed Event Scheduling, Rajiv Maheswaran, Milind Tambe, Emma Bowring, Jonathan Pearce, Pradeep Varakantham
Research Collection School Of Computing and Information Systems
Distributed Constraint Optimization (DCOP) is an elegant formalism relevant to many areas in multiagent systems, yet complete algorithms have not been pursued for real world applications due to perceived complexity. To capably capture a rich class of complex problem domains, we introduce the Distributed Multi-Event Scheduling (DiMES) framework and design congruent DCOP formulations with binary constraints which are proven to yield the optimal solution. To approach real-world efficiency requirements, we obtain immense speedups by improving communication structure and precomputing best case bounds. Heuristics for generating better communication structures and calculating bound in a distributed manner are provided and tested on …
Notes On Equilibria In Symmetric Games, Shih-Fen Cheng, Daniel M. Reeves, Yevgeniy Vorobeychik, Michael P. Wellman
Notes On Equilibria In Symmetric Games, Shih-Fen Cheng, Daniel M. Reeves, Yevgeniy Vorobeychik, Michael P. Wellman
Research Collection School Of Computing and Information Systems
In a symmetric game, every player is identical with respect to the game rules. We show that a symmetric 2strategy game must have a pure-strategy Nash equilibrium. We also discuss Nash’s original paper and its generalized notion of symmetry in games. As a special case of Nash’s theorem, any finite symmetric game has a symmetric Nash equilibrium. Furthermore, symmetric infinite games with compact, convex strategy spaces and continuous, quasiconcave utility functions have symmetric pure-strategy Nash equilibria. Finally, we discuss how to exploit symmetry for more efficient methods of finding Nash equilibria.
Modified Art 2a Growing Network Capable Of Generating A Fixed Number Of Nodes, Ji He, Ah-Hwee Tan, Chew-Lim Tan
Modified Art 2a Growing Network Capable Of Generating A Fixed Number Of Nodes, Ji He, Ah-Hwee Tan, Chew-Lim Tan
Research Collection School Of Computing and Information Systems
This paper introduces the Adaptive Resonance Theory under Constraint (ART-C 2A) learning paradigm based on ART 2A, which is capable of generating a user-defined number of recognition nodes through online estimation of an appropriate vigilance threshold. Empirical experiments compare the cluster validity and the learning efficiency of ART-C 2A with those of ART 2A, as well as three closely related clustering methods, namely online K-Means, batch K-Means, and SOM, in a quantitative manner. Besides retaining the online cluster creation capability of ART 2A, ART-C 2A gives the alternative clustering solution, which allows a direct control on the number of output …
Multi-Period Multi-Dimensional Knapsack Problem And Its Application To Available-To-Promise, Hoong Chuin Lau, M. K. Lim
Multi-Period Multi-Dimensional Knapsack Problem And Its Application To Available-To-Promise, Hoong Chuin Lau, M. K. Lim
Research Collection School Of Computing and Information Systems
This paper is motivated by a recent trend in logistics scheduling, called Available-to-Promise. We model this problem as the multi-period multi-dimensional knapsack problem. We provide some properties for a special case of a single-dimensional problem. Based on insights obtained from these properties, we propose a two-phase heuristics for solving the multi-dimensional problem. We also propose a novel time-based ant colony optimization algorithm. The quality of the solutions generated is verified through experiments, where we demonstrate that the computational time is superior compared with integer programming to achieve solutions that are within a small percentage of the upper bounds.
Stochastic Analysis And Performance Evaluation Of Wireless Schedulers, R. Rom, Hwee-Pink Tan
Stochastic Analysis And Performance Evaluation Of Wireless Schedulers, R. Rom, Hwee-Pink Tan
Research Collection School Of Computing and Information Systems
In the last few years, wireless scheduling algorithms have been proposed by supplementing wireline scheduling algorithms with a wireless adaptation scheme. However, Quality of Service (QoS) bounds have either been derived for flows that perceive error-free conditions or a static worst-case channel condition. Such an assumption of the channel condition is unrealistic, since channel errors are known to be bursty in nature. Hence, these bounds are inadequate to characterize the scheduler's QoS performance. Our research focuses on performing an extensive analysis of wireless scheduling in order to derive statistical QoS performance bounds under realistic channel conditions. In this paper, we …