“Network-Theoretic” Queuing Delay Estimation In Theme Park Attractions,
2013
Singapore Management University
“Network-Theoretic” Queuing Delay Estimation In Theme Park Attractions, Ajay Aravamudhan, Archan Misra, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
Queuing is a common phenomenon in theme parks which negatively affects visitor experience and revenue yields. There is thus a need for park operators to infer the real queuing delays without expensive investment in human effort or complex tracking infrastructure. In this paper, we depart from the classical queuing theory approach and provide a data-driven and online approach for estimating the time-varying queuing delays experienced at different attractions in a theme park. This work is novel in that it relies purely on empirical observations of the entry time of individual visitors at different attractions, and also accommodates the reality that …
Tesla: An Extended Study Of An Energy-Saving Agent That Leverages Schedule Flexibility,
2013
University of Southern California
Tesla: An Extended Study Of An Energy-Saving Agent That Leverages Schedule Flexibility, Jun Young Kwak, Pradeep Varakantham, Rajiv Maheswaran, Milind Tambe, Burcin Becerik-Gerber
Research Collection School Of Computing and Information Systems
This paper presents transformative energy-saving schedule-leveraging agent (TESLA), an agent for optimizing energy usage in commercial buildings. TESLA’s key insight is that adding flexibility to event/meeting schedules can lead to significant energy savings. This paper provides four key contributions: (i) online scheduling algorithms, which are at the heart of TESLA, to solve a stochastic mixed integer linear program for energy-efficient scheduling of incrementally/dynamically arriving meetings and events; (ii) an algorithm to effectively identify key meetings that lead to significant energy savings by adjusting their flexibility; (iii) an extensive analysis on energy savings achieved by TESLA; and (iv) surveys of real …
Collective Diffusion Over Networks: Models And Inference,
2013
Singapore Management University
Collective Diffusion Over Networks: Models And Inference, Akshat Kumar, Daniel Sheldon, Biplav Srivastava
Research Collection School Of Computing and Information Systems
Diffusion processes in networks are increasingly used to model the spread of information and social influence. In several applications in computational sustainability such as the spread of wildlife, infectious diseases and traffic mobility pattern, the observed data often consists of only aggregate information. In this work, we present new models that generalize standard diffusion processes to such collective settings. We also present optimization based techniques that can accurately learn the underlying dynamics of the given contagion process, including the hidden network structure, by only observing the time a node becomes active and the associated aggregate information. Empirically, our technique is …
Machines And The Moral Community,
2013
Ohio Northern University
Machines And The Moral Community, Erica L. Neely
Philosophy and Religion Faculty Scholarship
A key distinction in ethics is between members and nonmembers of the moral community. Over time, our notion of this community has expanded as we have moved from a rationality criterion to a sentience criterion for membership. I argue that a sentience criterion is insufficient to accommodate all members of the moral community; the true underlying criterion can be understood in terms of whether a being has interests. This may be extended to conscious, self-aware machines, as well as to any autonomous intelligent machines. Such machines exhibit an ability to formulate desires for the course of their own existence; this …
A Generic Decision Making Framework For Autonomous Systems,
2013
California Polytechnic State University, San Luis Obispo
A Generic Decision Making Framework For Autonomous Systems, Connor Lange
Master's Theses
With the rising popularity of small satellites, such as CubeSats, many smaller institutions previously incapable of developing and deploying a spacecraft have starting to do so. Institutions with a history of space flight, such as NASA JPL, have begun to put projects on CubeSats that would normally fly on much larger satellites. As a result, the institutions with space flight heritage have begun to port spacecraft software that was previously designed for much larger and more complex satellites to the CubeSat platform. Unfortunately for universities, who are the majority of all institutions devel- oping CubeSats, these ported systems are too …
Approximate Inference In Collective Graphical Models,
2013
University of Massachusetts Amherst
Approximate Inference In Collective Graphical Models, Daniel Sheldon, Tao Sun, Akshat Kumar, Thomas G. Dietterich
Research Collection School Of Computing and Information Systems
We study the problem of approximate inference in collective graphical models (CGMs), which were recently introduced to model the problem of learning and inference with noisy aggregate observations. We first analyze the complexity of inference in CGMs: unlike inference in conventional graphical models, exact inference in CGMs is NP-hard even for tree-structured models. We then develop a tractable convex approximation to the NP-hard MAP inference problem in CGMs, and show how to use MAP inference for approximate marginal inference within the EM framework. We demonstrate empirically that these approximation techniques can reduce the computational cost of inference by two orders …
Misheard Me Oronyminator: Using Oronyms To Validate The Correctness Of Frequency Dictionaries,
2013
California Polytechnic State University, San Luis Obispo
Misheard Me Oronyminator: Using Oronyms To Validate The Correctness Of Frequency Dictionaries, Jennifer G. Hughes
Master's Theses
In the field of speech recognition, an algorithm must learn to tell the difference between "a nice rock" and "a gneiss rock". These identical-sounding phrases are called oronyms. Word frequency dictionaries are often used by speech recognition systems to help resolve phonetic sequences with more than one possible orthographic phrase interpretation, by looking up which oronym of the root phonetic sequence contains the most-common words.
Our paper demonstrates a technique used to validate word frequency dictionary values. We chose to use frequency values from the UNISYN dictionary, which tallies each word on a per-occurance basis, using a proprietary text corpus, …
Understanding Sequential Decisions Via Inverse Reinforcement Learning,
2013
Carnegie Mellon University
Understanding Sequential Decisions Via Inverse Reinforcement Learning, Siyuan Liu, Miguel Araujo, Emma Brunskill, Rosaldo Rossetti, Joao Barros, Ramayya Krishnan
Research Collection School Of Computing and Information Systems
The execution of an agent's complex activities, comprising sequences of simpler actions, sometimes leads to the clash of conflicting functions that must be optimized. These functions represent satisfaction, short-term as well as long-term objectives, costs and individual preferences. The way that these functions are weighted is usually unknown even to the decision maker. But if we were able to understand the individual motivations and compare such motivations among individuals, then we would be able to actively change the environment so as to increase satisfaction and/or improve performance. In this work, we approach the problem of providing highlevel and intelligible descriptions …
Iterative Statistical Verification Of Probabilistic Plans,
2013
Lawrence University
Iterative Statistical Verification Of Probabilistic Plans, Colin M. Potts
Lawrence University Honors Projects
Artificial intelligence seeks to create intelligent agents. An agent can be anything: an autopilot, a self-driving car, a robot, a person, or even an anti-virus system. While the current state-of-the-art may not achieve intelligence (a rather dubious thing to quantify) it certainly achieves a sense of autonomy. A key aspect of an autonomous system is its ability to maintain and guarantee safety—defined as avoiding some set of undesired outcomes. The piece of software responsible for this is called a planner, which is essentially an automated problem solver. An advantage computer planners have over humans is their ability to consider and …
Modeling A Sensor To Improve Its Efficacy,
2013
University of Texas at Dallas
Modeling A Sensor To Improve Its Efficacy, Nabin K. Malakar, Daniil Gladkov, Kevin H. Knuth
Physics Faculty Scholarship
Robots rely on sensors to provide them with information about their surroundings. However, high-quality sensors can be extremely expensive and cost-prohibitive. Thus many robotic systems must make due with lower-quality sensors. Here we demonstrate via a case study how modeling a sensor can improve its efficacy when employed within a Bayesian inferential framework. As a test bed we employ a robotic arm that is designed to autonomously take its own measurements using an inexpensive LEGO light sensor to estimate the position and radius of a white circle on a black field. The light sensor integrates the light arriving from a …
Practical Tractability Of Csps By Higher Level Consistency And Tree Decomposition,
2013
University of Nebraska-Lincoln
Practical Tractability Of Csps By Higher Level Consistency And Tree Decomposition, Shant Karakashian
School of Computing: Dissertations, Theses, and Student Research
Constraint Satisfaction is a flexible paradigm for modeling many decision problems in Engineering, Computer Science, and Management. Constraint Satisfaction Problems (CSPs) are in general NP-complete and are usually solved with search. Research has identified various islands of tractability, which enable solving certain CSPs with backtrack-free search. For example, one sufficient condition for tractability relates the consistency level of a CSP to treewidth of the CSP's constraint network. However, enforcing higher levels of consistency on a CSP may require the addition of constraints, thus altering the topology of the constraint network and increasing its treewidth. This thesis addresses the following question: …
Hybrid Methods For Feature Selection,
2013
Western Kentucky University
Hybrid Methods For Feature Selection, Iunniang Cheng
Masters Theses & Specialist Projects
Feature selection is one of the important data preprocessing steps in data mining. The feature selection problem involves finding a feature subset such that a classification model built only with this subset would have better predictive accuracy than model built with a complete set of features. In this study, we propose two hybrid methods for feature selection. The best features are selected through either the hybrid methods or existing feature selection methods. Next, the reduced dataset is used to build classification models using five classifiers. The classification accuracy was evaluated in terms of the area under the Receiver Operating Characteristic …
Context-Driven Image Annotation Using Imagenet,
2013
Air Force Institute of Technology
Context-Driven Image Annotation Using Imagenet, George E. Noel, Gilbert L. Peterson
Faculty Publications
Image annotation research has demonstrated success on test data for focused domains. Unfortunately, extending these techniques to the broader topics found in real world data often results in poor performance. This paper proposes a novel approach that leverages WordNet and ImageNet capabilities to annotate images based on local text and image features. Signatures generated from ImageNet images based on WordNet synonymous sets are compared using Earth Mover's Distance against the query image and used to rank order surrounding words by relevancy. The results demonstrate effective image annotation, producing higher accuracy and improved specificity over the ALIPR image annotation system. Abstract …
Roulette Wheel Selection Game Player,
2013
Macalester College
Roulette Wheel Selection Game Player, Scott Tong
Mathematics, Statistics, and Computer Science Honors Projects
General Game Playing is a field of artificial intelligence that seeks to create programs capable of playing any game at an expert-level without the need for human aid. There are two major approaches to general game playing: simulation and heuristic. I focused on the move selection component of a common simulation strategy called Monte Carlo Tree Search. Traditionally, the selection step of Monte Carlo Tree Search uses an algorithm called Upper Confidence Bound Applied to Trees or UCT. In place of this algorithm, I investigated the applicability of a random roulette wheel style of selection. I studied the effectiveness of …
Disclosing Climate Change Patterns Using An Adaptive Markov Chain Pattern Detection Method,
2013
Singapore Management University
Disclosing Climate Change Patterns Using An Adaptive Markov Chain Pattern Detection Method, Zhaoxia Wang, Gary Lee, Hoong Maeng Chan, Reuben Li, Xiuju Fu, Rick Goh, Pauline A. W. Poh Kim, Martin L. Hibberd, Hoong Chor Chin
Research Collection School Of Computing and Information Systems
This paper proposes an adaptive Markov chain pattern detection (AMCPD) method for disclosing the climate change patterns of Singapore through meteorological data mining. Meteorological variables, including daily mean temperature, mean dew point temperature, mean visibility, mean wind speed, maximum sustained wind speed, maximum temperature and minimum temperature are simultaneously considered for identifying climate change patterns in this study. The results depict various weather patterns from 1962 to 2011 in Singapore, based on the records of the Changi Meteorological Station. Different scenarios with varied cluster thresholds are employed for testing the sensitivity of the proposed method. The robustness of the proposed …
Enabling Generative, Emergent Artificial Culture,
2013
Singapore Management University
Enabling Generative, Emergent Artificial Culture, Jaroslaw Kochanowicz, Ah-Hwee Tan, Daniel Thalmann
Research Collection School Of Computing and Information Systems
Despite the demand for culturally placed agent models, an adequate simulation approach to the relationship between group-cultural and individual-psychological qualities, including culture emergence, is just appearing. It could be argued that we are at the beginning of a domain forming process, a dawn of generative, emergent artificial culture. In this context we discuss current limitations and argue e.g. that too far reaching agent simplicity within Agent Based Modeling limits the emergence of realistic cultural-conventional level and we advocate psychologically rich models of culture forming mechanisms. We propose an approach to cultural phenomena modeling based on the interaction of habitual, affective …
Why Individuals Seek Diverse Opinions (Or Why They Don't),
2013
Singapore Management University
Why Individuals Seek Diverse Opinions (Or Why They Don't), Jisun An, Daniele Quercia, Jon Crowcroft
Research Collection School Of Computing and Information Systems
Fact checking has been hard enough to do in traditional settings, but, as news consumption is moving on the Internet and sources multiply, it is almost unmanageable. To solve this problem, researchers have created applications that expose people to diverse opinions and, as a result, expose them to balanced information. The wisdom of this solution is, however, placed in doubt by this paper. Survey responses of 60 individuals in the UK and South Korea and in-depth structured interviews of 10 respondents suggest that exposure to diverse opinions would not always work. That is partly because not all individuals equally value …
Distributed Gibbs: A Memory-Bounded Sampling-Based Dcop Algorithm,
2013
Singapore Management University
Distributed Gibbs: A Memory-Bounded Sampling-Based Dcop Algorithm, Duc Thien Nguyen, William Yeoh, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
Researchers have used distributed constraint optimization problems (DCOPs) to model various multi-agent coordination and resource allocation problems. Very recently, Ottens et al. proposed a promising new approach to solve DCOPs that is based on confidence bounds via their Distributed UCT (DUCT) sampling-based algorithm. Unfortunately, its memory requirement per agent is exponential in the number of agents in the problem, which prohibits it from scaling up to large problems. Thus, in this paper, we introduce a new sampling-based DCOP algorithm called Distributed Gibbs, whose memory requirements per agent is linear in the number of agents in the problem. Additionally, we show …
Implementation Of Slowly Changing Dimension To Data Warehouse To Manage Marketing Campaigns In Banks,
2013
Singapore Management University
Implementation Of Slowly Changing Dimension To Data Warehouse To Manage Marketing Campaigns In Banks, Lihui Wang, Junyu Choy, Michelle L. F. Cheong
Research Collection School Of Computing and Information Systems
Management of updating and recording campaign leads in data warehouse of any banking environment is complex especially with multiple campaigns are active simultaneously. As a way to avoid overly contacting customers for sales-based marketing contacts, the concept of Recency Frame is introduced to “lock” the customers who are targeted in Sales-based campaign for a specified time period. During this Recency Frame, the customer cannot be targeted by other Sales-based campaign under the same channel. This approach increased the difficulties of managing the customers’ data with proper data updating and storing and procedures have to be placed and made sufficiently robust …
Tesla: An Energy-Saving Agent That Leverages Schedule Flexibility,
2013
University of Southern California
Tesla: An Energy-Saving Agent That Leverages Schedule Flexibility, Jun Young Kwak, Pradeep Varakantham, Rajiv Maheswaran, Burcin Becerik-Gerber, Milind Tambe
Research Collection School Of Computing and Information Systems
This innovative application paper presents TESLA, an agent-based application for optimizing the energy use in commercial buildings. TESLA’s key insight is that adding flexibility to event/meeting schedules can lead to significant energy savings. TESLA provides three key contributions: (i) three online scheduling algorithms that consider flexibility of people’s preferences for energyefficient scheduling of incrementally/dynamically arriving meetings and events; (ii) an algorithm to effectively identify key meetings that lead to significant energy savings by adjusting their flexibility; and (iii) surveys of real users that indicate that TESLA’s assumptions exist in practice. TESLA was evaluated on data of over 110,000 meetings held …
