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Articles 8161 - 8190 of 8476
Full-Text Articles in Physical Sciences and Mathematics
Scaling Ant Colony Optimization With Hierarchical Reinforcement Learning Partitioning, Erik J. Dries
Scaling Ant Colony Optimization With Hierarchical Reinforcement Learning Partitioning, Erik J. Dries
Theses and Dissertations
This research merges the hierarchical reinforcement learning (HRL) domain and the ant colony optimization (ACO) domain. The merger produces a HRL ACO algorithm capable of generating solutions for both domains. This research also provides two specific implementations of the new algorithm: the first a modification to Dietterich's MAXQ-Q HRL algorithm, the second a hierarchical ACO algorithm. These implementations generate faster results, with little to no significant change in the quality of solutions for the tested problem domains. The application of ACO to the MAXQ-Q algorithm replaces the reinforcement learning, Q-learning and SARSA, with the modified ant colony optimization method, Ant-Q. …
Multi-Objective Optimization For Speed And Stability Of A Sony Aibo Gait, Christopher A. Patterson
Multi-Objective Optimization For Speed And Stability Of A Sony Aibo Gait, Christopher A. Patterson
Theses and Dissertations
Locomotion is a fundamental facet of mobile robotics that many higher level aspects rely on. However, this is not a simple problem for legged robots with many degrees of freedom. For this reason, machine learning techniques have been applied to the domain. Although impressive results have been achieved, there remains a fundamental problem with using most machine learning methods. The learning algorithms usually require a large dataset which is prohibitively hard to collect on an actual robot. Further, learning in simulation has had limited success transitioning to the real world. Also, many learning algorithms optimize for a single fitness function, …
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 …
Proceedings Of The 18th Irish Conference On Artificial Intelligence And Cognitive Science, Sarah Jane Delany, Michael Madden
Proceedings Of The 18th Irish Conference On Artificial Intelligence And Cognitive Science, Sarah Jane Delany, Michael Madden
Books/Book Chapters
These proceedings contain the papers that were accepted for publication at AICS-2007, the 18th Annual Conference on Artificial Intelligence and Cognitive Science, which was held in the Technological University Dublin; Dublin, Ireland; on the 29th to the 31st August 2007. AICS is the annual conference of the Artificial Intelligence Association of Ireland (AIAI).
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 …
Genetic Evolution Of Hierarchical Behavior Structures, Brian G. Woolley, Gilbert L. Peterson
Genetic Evolution Of Hierarchical Behavior Structures, Brian G. Woolley, Gilbert L. Peterson
Faculty Publications
The development of coherent and dynamic behaviors for mobile robots is an exceedingly complex endeavor ruled by task objectives, environmental dynamics and the interactions within the behavior structure. This paper discusses the use of genetic programming techniques and the unified behavior framework to develop effective control hierarchies using interchangeable behaviors and arbitration components. Given the number of possible variations provided by the framework, evolutionary programming is used to evolve the overall behavior design. Competitive evolution of the behavior population incrementally develops feasible solutions for the domain through competitive ranking. By developing and implementing many simple behaviors independently and then evolving …
An Artificial Immune System-Inspired Multiobjective Evolutionary Algorithm With Application To The Detection Of Distributed Computer Network Intrusions, Charles R. Haag, Gary B. Lamont, Paul D. L. Williams, Gilbert L. Peterson
An Artificial Immune System-Inspired Multiobjective Evolutionary Algorithm With Application To The Detection Of Distributed Computer Network Intrusions, Charles R. Haag, Gary B. Lamont, Paul D. L. Williams, Gilbert L. Peterson
Faculty Publications
Today's signature-based intrusion detection systems are reactive in nature and storage-limited. Their operation depends upon catching an instance of an intrusion or virus and encoding it into a signature that is stored in its anomaly database, providing a window of vulnerability to computer systems during this time. Further, the maximum size of an Internet Protocol-based message requires the database to be huge in order to maintain possible signature combinations. In order to tighten this response cycle within storage constraints, this paper presents an innovative Artificial Immune System-inspired Multiobjective Evolutionary Algorithm. This distributed intrusion detection system (IDS) is intended to measure …
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.
Leaf: A Learning-Based Fault Diagnostic System For Multi-Robot Teams, Balajee Kannan
Leaf: A Learning-Based Fault Diagnostic System For Multi-Robot Teams, Balajee Kannan
Doctoral Dissertations
The failure-prone complex operating environment of a standard multi-robot application dictates some amount of fault-tolerance to be incorporated into every system. In fact, the quality of the incorporated fault-tolerance has a direct impact on the overall performance of the system. Despite the extensive work being done in the field of multi-robot systems, there does not exist a general methodology for fault diagnosis and recovery. The objective of this research, in part, is to provide an adaptive approach that enables the robot team to autonomously detect and compensate for the wide variety of faults that could be experienced. The key feature …
Wide Area Search And Engagement Simulation Validation, Michael J. Marlin
Wide Area Search And Engagement Simulation Validation, Michael J. Marlin
Theses and Dissertations
As unmanned aerial vehicles (UAVs) increase in capability, the ability to refuel them in the air is becoming more critical. Aerial refueling will extend the range, shorten the response times, and extend loiter time of UAVs. Executing aerial refueling autonomously will reduce the command and control, logistics, and training efforts associated with fielding UAV systems. Currently, the Air Force Research Lab is researching the various technologies required to conduct automated aerial refueling (AAR). One of the required technologies is the ability to autonomously rendezvous with the tanker. The goal of this research is to determine the control required to fly …
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 …
Multi-Robot Fastslam For Large Domains, Choyong G. Koperski
Multi-Robot Fastslam For Large Domains, Choyong G. Koperski
Theses and Dissertations
For a robot to build a map of its surrounding area, it must have accurate position information within the area, and to obtain accurate position information within the area, the robot needs to have an accurate map of the area. This circular problem is the Simultaneous Localization and Mapping (SLAM) problem. An efficient algorithm to solve it is FastSLAM, which is based on the Rao-Blackwellized particle filter. FastSLAM solves the SLAM problem for single-robot mapping using particles to represent the posterior of the robot pose and the map. Each particle of the filter possesses its own global map which is …
Performance Evaluation Of Ad Hoc Routing In A Swarm Of Autonomous Aerial Vehicles, Matthew T. Hyland
Performance Evaluation Of Ad Hoc Routing In A Swarm Of Autonomous Aerial Vehicles, Matthew T. Hyland
Theses and Dissertations
This thesis investigates the performance of three mobile ad hoc routing protocols in the context of a swarm of autonomous unmanned aerial vehicles (UAVs). It is proposed that a wireless network of nodes having an average of 5.1774 log n neighbors, where n is the total number of nodes in the network, has a high probability of having no partitions. By decreasing transmission range while ensuring network connectivity, and implementing multi-hop routing between nodes, spatial multiplexing is exploited whereby multiple pairs of nodes simultaneously transmit on the same channel. The proposal is evaluated using the Greedy Perimeter Stateless Routing (GPSR), …
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 …
Multi-Robot-Based Nanoassembly Planning With Automated Path Generation, Xiaobu Yuan, Simon X. Yang
Multi-Robot-Based Nanoassembly Planning With Automated Path Generation, Xiaobu Yuan, Simon X. Yang
Computer Science Publications
In this paper, a novel approach of automated multirobot nanoassembly planning is presented. This approach uses an improved self-organizing map to coordinate assembly tasks of nanorobots while generating optimized motion paths at run time with a modified shunting neural network. It is capable of synchronizing multiple nanorobots working simultaneously and efficiently on the assembly of swarms of objects in the presence of obstacles and environmental uncertainty. Operation of the presented approach is demonstrated with experiments at the end of the paper.
Actors, Objects, Contextures, Morphograms, Rudolf Kaehr
Actors, Objects, Contextures, Morphograms, Rudolf Kaehr
Rudolf Kaehr
Systematic and historic overview and critics of actor and object oriented programming.
From Dialogues To Polylogues, Rudolf Kaehr
Michael Wheeler: Reconstructing The Cognitive World: The Next Step, Leslie Marsh
Michael Wheeler: Reconstructing The Cognitive World: The Next Step, Leslie Marsh
Leslie Marsh
Michael Wheeler is the latest in a new wave of philosophical theorists that fall within a loose coalition of anti-representationalism (or anti-Cartesianism): Dynamical –, Embodied –, Extended –, Distributed –, and Situated –, theories of cognition (DEEDS an apt acronym). Against this background, cognition for Wheeler is, or should be, a more ecumenical concept. This ecumenical approach would still be amenable to making theoretical distinctions, the central one being the notion of offline and online styles of intelligence, a distinction that makes conceptual space for another closely related notion, that of propositional knowledge (knowing that) and tacit knowledge (knowing how).
Proceedings Of The 4th Acl-Sigsem Workshop On Prepositions At Acl-2007., Fintan Costello, John D. Kelleher, Martin Volk
Proceedings Of The 4th Acl-Sigsem Workshop On Prepositions At Acl-2007., Fintan Costello, John D. Kelleher, Martin Volk
Conference papers
This volume contains the papers presented at the Fourth ACL-SIGSEM Workshop on Prepositions. This workshop is endorsed by the ACL Special Interest Group on Semantics (ACL-SIGSEM), and is hosted in conjunction with ACL 2007, taking place on 28th June, 2007 in Prague, the Czech Republic.
A Classifier To Evaluate Language Specificity In Medical Documents, Trudi Miller '08, Gondy A. Leroy, Samir Chatterjee, Jie Fan, Brian Thoms '09
A Classifier To Evaluate Language Specificity In Medical Documents, Trudi Miller '08, Gondy A. Leroy, Samir Chatterjee, Jie Fan, Brian Thoms '09
CGU Faculty Publications and Research
Consumer health information written by health care professionals is often inaccessible to the consumers it is written for. Traditional readability formulas examine syntactic features like sentence length and number of syllables, ignoring the target audience's grasp of the words themselves. The use of specialized vocabulary disrupts the understanding of patients with low reading skills, causing a decrease in comprehension. A naive Bayes classifier for three levels of increasing medical terminology specificity (consumer/patient, novice health learner, medical professional) was created with a lexicon generated from a representative medical corpus. Ninety-six percent accuracy in classification was attained. The classifier was then applied …
Using Computer Vision To Create A 3d Representation Of A Snooker Table For Televised Competition Broadcasting, Hao Guo, Brian Mac Namee
Using Computer Vision To Create A 3d Representation Of A Snooker Table For Televised Competition Broadcasting, Hao Guo, Brian Mac Namee
Conference papers
The Snooker Extraction and 3D Builder (SE3DB) is designed to be used as a viewer aid in televised snooker broadcasting. Using a single camera positioned over a snooker table, the system creates a virtual 3D model of the table which can be used to allow audiences view the table from any angle. This would be particularly useful in allowing viewers to determine if particular shots are possible or not. This paper will describe the design, development and evaluation of this system. Particular focus in the paper will be given to the techniques used to recognise and locate the balls on …
A New Member Of The Family? The Continuum Of Being, Artificial Intelligence, And The Image Of God, Noreen L. Herzfeld
A New Member Of The Family? The Continuum Of Being, Artificial Intelligence, And The Image Of God, Noreen L. Herzfeld
Theology Faculty Publications
Are the scientific and religious definitions of life irreconcilable or do they overlap in significant areas? What is life? Religion seems to imply that there is a qualitative distinction between human beings and the rest of creation; however, there is a strong tradition in Christianity and in Eastern thought that suggests that the natural world also has a relationship with God. Human dominion over other parts of creation exists, but does not obviate this connection, nor give humans a circle unto themselves. The concept of humans being created in the image of God can be used to explain why we …
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 …
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 …
Frequency Based Incremental Attribute Selection For Gre., John D. Kelleher
Frequency Based Incremental Attribute Selection For Gre., John D. Kelleher
Conference papers
The DIT system uses an incremental greedy search to generate descriptions, similar to the incremental algorithm described in (Dale and Reiter, 1995). The selection of the next attribute to be tested for inclusion in the description is ordered by the absolute frequency of each attribute in the training corpus. Attributes are selected in descending order of frequency (i.e. the attribute that occurred most frequently in the training corpus is selected first). Where two or more attributes have the same frequency of occurrence the first attribute found with that frequency is selected. The type attribute is always included in the description. …
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 …
Using Machine Learning Techniques To Create Ai Controlled Players For Video Games, Bhuman Soni
Using Machine Learning Techniques To Create Ai Controlled Players For Video Games, Bhuman Soni
Theses : Honours
This study aims to achieve higher replay and entertainment value in a game through human-like AI behaviour in computer controlled characters called bats. In order to achieve that, an artificial intelligence system capable of learning from observation of human player play was developed. The artificial intelligence system makes use of machine learning capabilities to control the state change mechanism of the bot. The implemented system was tested by an audience of gamers and compared against bats controlled by static scripts. The data collected was focused on qualitative aspects of replay and entertainment value of the game and subjected to quantitative …