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- Crisis management (1)
- Decision tree (1)
- Earliness-tardiness (1)
- Event understanding (1)
- Fuzzy controller (1)
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- Image feature discretization (1)
- Image semantic learning (1)
- Meta-heuristics (1)
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- Military warehouse (1)
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- Rushes video summarization (1)
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Articles 1 - 15 of 15
Full-Text Articles in Physical Sciences and Mathematics
Tuning Tabu Search Strategies Via Visual Diagnosis, Steven Halim, Hoong Chuin Lau
Tuning Tabu Search Strategies Via Visual Diagnosis, Steven Halim, 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 …
Designing The Market Game For A Commodity Trading Simulation, Shih-Fen Cheng
Designing The Market Game For A Commodity Trading Simulation, Shih-Fen Cheng
Research Collection School Of Computing and Information Systems
In this paper, we propose to design a market game that (a) can be used in modeling and studying commodity trading scenarios, and (b) can be used in capturing human traders' behaviors. Specifically, we demonstrate the usefulness of this commodity trading game in a single-commodity futures trading scenario. A pilot experiment was run with a mixture of human traders and an autonomous agent that emulates the aggregatedmarket condition, with the assumption that this autonomous agent would hint each of its action through a public announcement. We show that the information collected from this simulation can be used to extract the …
Multi-Period Combinatorial Auction Mechanism For Distributed Resource Allocation And Scheduling, Hoong Chuin Lau, Shih-Fen Cheng, Thin Yin Leong, Jong Han Park, Zhengyi Zhao
Multi-Period Combinatorial Auction Mechanism For Distributed Resource Allocation And Scheduling, Hoong Chuin Lau, Shih-Fen Cheng, Thin Yin Leong, Jong Han Park, Zhengyi Zhao
Research Collection School Of Computing and Information Systems
We consider the problem of resource allocation and scheduling where information and decisions are decentralized, and our goal is to propose a market mechanism that allows resources from a central resource pool to be allocated to distributed decision makers (agents) that seek to optimize their respective scheduling goals. We propose a generic combinatorial auction mechanism that allows agents to competitively bid for the resources needed in a multi-period setting, regardless of the respective scheduling problem faced by the agent, and show how agents can design optimal bidding strategies to respond to price adjustment strategies from the auctioneer. We apply our …
The Price Of Stability In Selfish Scheduling Games, Lucas Agussurja, Hoong Chuin Lau
The Price Of Stability In Selfish Scheduling Games, Lucas Agussurja, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
Game theory has gained popularity as an approach to analysing and understanding distributed systems with selfinterested agents. Central to game theory is the concept of Nash equilibrium as a stable state (solution) of the system, which comes with a price - the loss in efficiency. The quantification of the efficiency loss is one of the main research concerns. In this paper, we study the quality and computational characteristic of the best Nash equilibrium in two selfish scheduling models: the congestion model and the sequencing model. In particular, we present the following results: (1) In the congestion model: first, the best …
Robust Local Search And Its Application To Generating Robust Schedules, Hoong Chuin Lau, Fei Xiao, Thomas Ou
Robust Local Search And Its Application To Generating Robust Schedules, Hoong Chuin Lau, Fei Xiao, Thomas Ou
Research Collection School Of Computing and Information Systems
In this paper, we propose an extended local search framework to solve combinatorial optimization problems with data uncertainty. Our approach represents a major departure from scenario-based or stochastic programming approaches often used to tackle uncertainty. Given a value 0 < ? 1, we are interested to know what the robust objective value is, i.e. the optimal value if we allow an chance of not meeting it, assuming that certain data values are defined on bounded random variables. We show how a standard local search or metaheuristic routine can be extended to efficiently construct a decision rule with such guarantee, albeit heuristically. We demonstrate its practical applicability on the Resource Constrained Project Scheduling Problem with minimal and maximal time lags (RCPSP/max) taking into consideration activity duration uncertainty. Experiments show that, partial order schedules can be constructed that are robust in our sense without the need for a large planned horizon (due date), which improves upon the work proposed by Policella et al. 2004.
Rushes Video Summarization By Object And Event Understanding, Feng Wang, Chong-Wah Ngo
Rushes Video Summarization By Object And Event Understanding, Feng Wang, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
This paper explores a variety of visual and audio analysis techniques in selecting the most representative video clips for rushes summarization at TRECVID 2007. These techniques include object detection, camera motion estimation, keypoint matching and tracking, audio classification and speech recognition. Our system is composed of two major steps. First, based on video structuring, we filter undesirable shots and minimize the inter-shot redundancy by repetitive shot detection. Second, a representability measure is proposed to model the presence of objects and four audio-visual events: motion activity of objects, camera motion, scene changes, and speech content, in a video clip. The video …
An Artificial Immune System Based Approach For English Grammar Correction, Akshat Kumar, Shivashankar B. Nair
An Artificial Immune System Based Approach For English Grammar Correction, Akshat Kumar, Shivashankar B. Nair
Research Collection School Of Computing and Information Systems
Grammar checking and correction comprise of the primary problems in the area of Natural Language Processing (NLP). Traditional approaches fall into two major categories: Rule based and Corpus based. While the former relies heavily on grammar rules the latter approach is statistical in nature. We provide a novel corpus based approach for grammar checking that uses the principles of an Artificial Immune System (AIS).We treat grammatical error as pathogens (in immunological terms) and build antibody detectors capable of detecting grammatical errors while allowing correct constructs to filter through. Our results show that it is possible to detect a range of …
Generating Job Schedules For Vessel Operations In A Container Terminal, Thin Yin Leong, Hoong Chuin Lau
Generating Job Schedules For Vessel Operations In A Container Terminal, Thin Yin Leong, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
No abstract provided.
Designing An Experimental Gaming Platform For Trading Grid Resources, Danny Oh, Shih-Fen Cheng, Dan Ma, Ravi Bapna
Designing An Experimental Gaming Platform For Trading Grid Resources, Danny Oh, Shih-Fen Cheng, Dan Ma, Ravi Bapna
Research Collection School Of Computing and Information Systems
This paper describes our current work in designing an experimental gaming platform for simulating the trading of grid resources. The open platform allows researchers in grid economics to experiment with different market structures and pricing models. We would be using a design science approach in the implementation. Key design considerations and an overview of the functional design of the platform are presented and discussed.
Efficient Algorithms For Machine Scheduling Problems With Earliness And Tardiness Penalties, Guang Feng, Hoong Chuin Lau
Efficient Algorithms For Machine Scheduling Problems With Earliness And Tardiness Penalties, Guang Feng, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
In this paper, we study the multi-machine scheduling problem with earliness and tardiness penalties and sequence dependent setup times. This problem can be decomposed into two subproblems—sequencing and timetabling. Sequencing focuses on assigning each job to a fixed machine and determine the job sequence on each machine. We call such assignment a semi-schedule. Timetabling focuses on finding an executable schedule from the semi-schedule via idle-time insertion. Sequencing is strongly NP-hard in general. Although timetabling is polynomial-time solvable, it can become a computational bottleneck if the procedure is executed many times within a larger framework. This paper makes two contributions. We …
Towards Efficient Planning For Real World Partially Observable Domains, Pradeep R. Varakantham
Towards Efficient Planning For Real World Partially Observable Domains, Pradeep R. Varakantham
Research Collection School Of Computing and Information Systems
My research goal is to build large-scale intelligent systems (both single- and multi-agent) that reason with uncertainty in complex, real-world environments. I foresee an integration of such systems in many critical facets of human life ranging from intelligent assistants in hospitals to offices, from rescue agents in large scale disaster response to sensor agents tracking weather phenomena in earth observing sensor webs, and others. In my thesis, I have taken steps towards achieving this goal in the context of systems that operate in partially observable domains that also have transitional (non-deterministic outcomes to actions) uncertainty. Given this uncertainty, Partially Observable …
Iterated Weaker-Than-Weak Dominance, Shih-Fen Cheng, Michael P. Wellman
Iterated Weaker-Than-Weak Dominance, Shih-Fen Cheng, Michael P. Wellman
Research Collection School Of Computing and Information Systems
We introduce a weakening of standard gametheoretic δ-dominance conditions, called dominance, which enables more aggressive pruning of candidate strategies at the cost of solution accuracy. Equilibria of a game obtained by eliminating a δ-dominated strategy are guaranteed to be approximate equilibria of the original game, with degree of approximation bounded by the dominance parameter. We can apply elimination of δ-dominated strategies iteratively, but the for which a strategy may be eliminated depends on prior eliminations. We discuss implications of this order independence, and propose greedy heuristics for determining a sequence of eliminations to reduce the game as far as possible …
Integrating Semantic Templates With Decision Tree For Image Semantic Learning, Ying Liu, Dengsheng Zhang, Guojun Lu, Ah-Hwee Tan
Integrating Semantic Templates With Decision Tree For Image Semantic Learning, Ying Liu, Dengsheng Zhang, Guojun Lu, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
Decision tree (DT) has great potential in image semantic learning due to its simplicity in implementation and its robustness to incomplete and noisy data. Decision tree learning naturally requires the input attributes to be nominal (discrete). However, proper discretization of continuous-valued image features is a difficult task. In this paper, we present a decision tree based image semantic learning method, which avoids the difficult image feature discretization problem by making use of semantic template (ST) defined for each concept in our database. A ST is the representative feature of a concept, generated from the low-level features of a collection of …
Towards Efficient Computation Of Quality Bounded Solutions In Pomdps: Expected Value Approximation And Dynamic Disjunctive Beliefs, Pradeep Reddy Varakantham, Rajiv Maheswaran, Tapana Gupta, Milind Tambe
Towards Efficient Computation Of Quality Bounded Solutions In Pomdps: Expected Value Approximation And Dynamic Disjunctive Beliefs, Pradeep Reddy Varakantham, Rajiv Maheswaran, Tapana Gupta, Milind Tambe
Research Collection School Of Computing and Information Systems
While POMDPs (partially observable markov decision problems) are a popular computational model with wide-ranging applications, the computational cost for optimal policy generation is prohibitive. Researchers are investigating ever-more efficient algorithms, yet many applications demand such algorithms bound any loss in policy quality when chasing efficiency. To address this challenge, we present two new techniques. The first approximates in the value space to obtain solutions efficiently for a pre-specified error bound. Unlike existing techniques, our technique guarantees the resulting policy will meet this bound. Furthermore, it does not require costly computations to determine the quality loss of the policy. Our second …
Real-Time Supply Chain Control Via Multi-Agent Adjustable Autonomy, Hoong Chuin Lau, Lucas Agussurja, Ramesh Thangarajoo
Real-Time Supply Chain Control Via Multi-Agent Adjustable Autonomy, Hoong Chuin Lau, Lucas Agussurja, Ramesh Thangarajoo
Research Collection School Of Computing and Information Systems
Real-time supply chain management in a rapidly changing environment requires reactive and dynamic collaboration among participating entities. In this work, we model supply chain as a multi-agent system where agents are subject to an adjustable autonomy. The autonomy of an agent refers to its capability to make and influence decisions within a multi-agent system. Adjustable autonomy means changing the autonomy of the agents during runtime as a response to changes in the environment. In the context of a supply chain, different entities will have different autonomy levels and objective functions as the environment changes, and the goal is to design …