Artificial Intelligence and Robotics Commons^™

A Method For Introducing Artificial Perception (Ap) To Improve Human Behavior Representation (Hbr) Using Agents In Synthetic Environments, Randall Bartholomew Garrett

Computational Modeling & Simulation Engineering Theses & Dissertations

While psychology has shown that perception is very important for the human decision process, agent perception has not been covered in sufficient detail within the agent directed simulation field. To contribute to such a solution, an open challenge lies in capturing the knowledge of human sciences, such as psychology, and making this knowledge usable for engineers. This dissertation addresses perception by describing an experimental method where agent perception simulates human perception. In particular, it presents engineering methods based on accepted psychological approaches resulting in a proof of concept. To prove the feasibility, an Artificial Perception (AP) meta-model is presented using …

Tree-D-Seek: A Framework For Retrieving Three-Dimensional Scenes, Saurav Mazumdar

Electrical & Computer Engineering Theses & Dissertations

In this dissertation, a strategy and framework for retrieving 3D scenes is proposed. The strategy is to retrieve 3D scenes based on a unified approach for indexing content from disparate information sources and information levels. The TREE-D-SEEK framework implements the proposed strategy for retrieving 3D scenes and is capable of indexing content from a variety of corpora at distinct information levels. A semantic annotation model for indexing 3D scenes in the TREE-D-SEEK framework is also proposed. The semantic annotation model is based on an ontology for rapid prototyping of 3D virtual worlds.

With ongoing improvements in computer hardware and 3D …

Optimizing Service Systems Based On Application-Level Qos, Qianhui Liang, Xindong Wu, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Making software systems service-oriented is becoming the practice, and an increasingly large number of service systems play important roles in today's business and industry. Currently, not enough attention has been paid to the issue of optimization of service systems. In this paper, we argue that the key elements to be considered in optimizing service systems are robustness, system orientation, and being dynamic and transparent. We present our solution to optimizing service systems based on application-level QoS management. Our solution incorporates three capabilities, i.e., 1) the ability to cater to the varying rigidities on Web service QoS in distinct application domains …

Describing Fuzzy Sets Using A New Concept: Fuzzify Functor, Kexin Wei, Zhaoxia Wang, Quan Wang

Research Collection School Of Computing and Information Systems

This paper proposed a fuzzify functor as an extension of the concept of fuzzy sets. The fuzzify functor and the first-order operated fuzzy set are defined. From the theory analysis, it can be observed that when the fuzzify functor acts on a simple crisp set, we get the first order fuzzy set or type-1 fuzzy set. By operating the fuzzify functor on fuzzy sets, we get the higher order fuzzy sets or higher type fuzzy sets and their membership functions. Using the fuzzify functor we can exactly describe the type-1 fuzzy sets, type-2 fuzzy sets and higher type or higher …

Pioneering The Personal Robotics Industry, Russell Nickerson

Undergraduate Review

The up and coming industry that I will be reporting about here is the personal and home robotics industry. I will show how the development cycle in the United States functions. I will then answer the question: What are the main limits that hold back this industry? The U.S. approach to robotics will be contrasted with Japan’s approach as Japan has another very well developed robotics program.

Fable: Finite Automata Based Learning Engine, Ryan Michael Jackson

Theses Digitization Project

The purpose of this thesis will be to demostrate the feasibility of building a system that is capable of automatically learning how to increase performance at a task that is presented to it by means of modeling the problem with a finite automation and the learning engine of FABLE. Current work in the field of automatic learning of FA's (Finite Automation) is mostly focused on the building of the FA itself. This thesis will instead focus on the automated building of FA models to allow better decisions to be made in the future.

Maze Maps & Benchmark Problems, Nathan R. Sturtevant

Moving AI Lab: 2D Maps and Benchmark Problems

Contains 60 maps of size 512x512 and benchmark problem sets. These maps are algorithm-generated mazes with corridor widths of 1, 2, 4, 8, 16, or 32. There are 10 maps and problem sets for each corridor size.

Room Maps & Benchmark Problems, Nathan R. Sturtevant

Moving AI Lab: 2D Maps and Benchmark Problems

Contains 40 maps of size 512x512 and problem sets. Maps are divided into rooms of size 8x8, 16x16, 32x32, and 64x64. There are 10 maps and problem sets for each room size. Maps with differing room sizes are not scaled: thickness of walls and passages differs.

Random Obstacle Maps & Benchmark Problems, Nathan R. Sturtevant

Moving AI Lab: 2D Maps and Benchmark Problems

Contains 70 maps of size 512x512 and benchmark problem sets. These maps are algorithm-generated by blocking grid cells. Maps contain 10%, 15%, 20%, 25%, 30%, 35%, or 40% blocked cells. There are 10 maps and problem sets for each percentage.

The Good, The Bad And The Incorrectly Classified: Profiling Cases For Case-Base Editing, Sarah Jane Delany

Conference papers

Case-based approaches to classification, as instance-based learning techniques, have a particular reliance on training examples that other supervised learning techniques do not have. In this paper we present the RDCL case profiling technique that categorises each case in a case-base based on its classification by the case-base, the benefit it has and/or the damage it causes by its inclusion in the case-base. We show how these case profiles can identify the cases that should be removed from a case-base in order to improve generalisation accuracy and we show what aspects of existing noise reduction algorithms contribute to good performance and …

Machine Learned Melody Matching Using Strictly Relative Musical Abstractions, Michael Joseph Kolta

Legacy Theses & Dissertations (2009 - 2024)

We implement and evaluate a machine learning approach to improve systems for searching a database of music via melodic sample. We explore symbolic and aural input queries and test our prototypes with extensive user surveys. Our main contribution is to combine the following four elements. First is to create a unique musical abstraction that accounts for both pitch and rhythm in a relative manner. Second, our system allows for approximate matching of imperfect queries via the utilization of the Smith-Waterman algorithm that was originally designed for approximate matching of molecular subsequences, such as DNA samples. Third is to design our …

Widening The Evaluation Net, Brian Mac Namee, Mark Dunne

Conference papers

Intelligent Virtual Agent (IVA) systems are notoriously difficult to evaluate, particularly due to the subjectivity involved. From the various efforts to develop standard evaluation schemes for IVA systems the scheme proposed by Isbister & Doyle, which evaluates systems across five categories, seems particularly appropriate. To examine how these categories are being used, the evaluations presented in the proceedings of IVA '07 and IVA '08 are summarised and the extent to which the five categories in the Isbister & Doyle scheme are used is highlighted. Finally, to illustrate how the full scheme can be used, an evaluation of an IVA system …

Stepping Off The Stage, Brian Mac Namee, John D. Kelleher

Conference papers

Mixed-reality virtual agents are an attractive solution to the problems associated with human-robot interaction, allowing all the expressiveness of virtual characters to be married with the advantages of a physical artifact which exists in a shared environment with the user. However, common approaches to achieving this restrict the virtual characters appearing on top of, or encompassing the robot. This paper describes the Stepping Off the Stage system in which mixed-reality agents are allowed to step off the robot stage and move to other parts of the environment, offering compelling new interaction possibilities.

Sampling With Confidence: Using K-Nn Confidence Measures In Active Learning, Rong Hu, Sarah Jane Delany, Brian Macnamee

Conference papers

Active learning is a process through which classifiers can be built from collections of unlabelled examples through the cooperation of a human oracle who can label a small number of examples selected as most informative. Typically the most informative examples are selected through uncertainty sampling based on classification scores. However, previous work has shown that, contrary to expectations, there is not a direct relationship between classification scores and classification confidence. Fortunately, there exists a collection of particularly effective techniques for building measures of classification confidence from the similarity information generated by k-NN classifiers. This paper investigates using these confidence measures …

Forked:A Demonstration Of Physics Realism In Augmented Reality, David Beaney, Brian Mac Namee

Conference papers

In making fully immersive augmented reality (AR) applications, real and virtual objects will have to be seen to physically interact together in a realistic and believable way. This paper describes Forked! a system that has been developed to show how physical interactions between real and virtual objects can be simulated re- alistically and believably through appropriate use of a physics en- gine. The system allows users control a robotic forklift to manipu- late virtual crates in an AR environment. The paper also describes a evaluation experiment in which it is shown that the physical inter- actions between the forklift and …

A Fuzzy Hierarchical Decision Model And Its Application In Networking Datacenters And In Infrastructure Acquisitions And Design, Michael Khader

Walden Dissertations and Doctoral Studies

According to several studies, an inordinate number of major business decisions to acquire, design, plan, and implement networking infrastructures fail. A networking infrastructure is a collaborative group of telecommunications systems providing services needed for a firm's operations and business growth. The analytical hierarchy process (AHP) is a well established decision-making process used to analyze decisions related to networking infrastructures. AHP is concerned with decomposing complex decisions into a set of factors and solutions. However, AHP has difficulties in handling uncertainty in decision information. This study addressed the research question of solutions to AHP deficiencies. The solutions were accomplished through the …

Locating And Tracking Objects By Efficient Comparison Of Real And Predicted Synthetic Video Imagery, Damian M. Lyons, D. Paul Benjamin

CSIS Technical Reports

The paper uses a 3D simulation engine to generate predicted imagery for tracking objects with complex behavior and compares that imagery against real video. Salient points and an affine transformation align real and synthetic scenes so that synchronization differences are suppressed and meaningful content differences are emphasized.

Event-Detecting Multi-Agent Mdps: Complexity And Constant-Factor Approximation, Akshat Kumar, S. Zilberstein

Research Collection School Of Computing and Information Systems

Planning under uncertainty for multiple agents has grown rapidly with the development of formal models such as multi-agent MDPs and decentralized MDPs. But despite their richness, the applicability of these models remains limited due to their computational complexity. We present the class of event-detecting multi-agent MDPs (eMMDPs), designed to detect multiple mobile targets by a team of sensor agents. We show that eMMDPs are NP-Hard and present a scalable 2-approximation algorithm for solving them using matroid theory and constraint optimization. The complexity of the algorithm is linear in the state-space and number of agents, quadratic in the horizon, and exponential …

Ontology-Based Business Process Customization For Composite Web Services, Qianhui (Althea) Liang, Xindong Wu, E. K. Park, T. Khoshgoftaar, C. Chi

Research Collection School Of Computing and Information Systems

A key goal of the Semantic Web is to shift social interaction patterns from a producer-centric paradigm to a consumer-centric one. Treating customers as the most valuable assets and making the business models work better for them are at the core of building successful consumer-centric business models. It follows that customizing business processes constitutes a major concern in the realm of a knowledge-pull-based human semantic Web. This paper conceptualizes the customization of service-based business processes leveraging the existing knowledge of Web services and business processes. We represent this conceptualization as a new Extensible Markup Language (XML) markup language Web Ontology …

Integrated Resource Allocation And Scheduling In Bidirectional Flow Shop With Multi-Machine And Cos Constraints, Hoong Chuin Lau, Zhengyi Zhao, Shuzhi Sam Ge

Research Collection School Of Computing and Information Systems

An integer programming (IP) model is proposed for integrated resource allocation and operation scheduling for a multiple job-agents system. Each agent handles a specific job-list in a bidirectional flowshop. For the individual agent scheduling problem, a formulation is proposed in continuous time domain and compared with an IP formulation in discrete time domain. Of particular interest is the formulation of the machine utilization function-- both in continuous time and discrete time. Fast heuristic methods are proposed with the relaxation of the machine capacity. For the integrated resource allocation and scheduling problem, a linear programming relaxation approach is applied to solve …

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 self-interested 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 characteristics 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 …