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Artificial Intelligence and Robotics

2013

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Articles 61 - 90 of 133

Full-Text Articles in Physical Sciences and Mathematics

Lagrangian Relaxation For Large-Scale Multi-Agent Planning, Geoff Gordon, Pradeep Varakantham, William Yeoh, Hoong Chuin Lau, Shih-Fen Cheng May 2013

Lagrangian Relaxation For Large-Scale Multi-Agent Planning, Geoff Gordon, Pradeep Varakantham, William Yeoh, Hoong Chuin Lau, Shih-Fen Cheng

Shih-Fen Cheng

Multi-agent planning is a well-studied problem with various applications including disaster rescue, urban transportation and logistics, both for autonomous agents and for decision support to humans. Due to computational constraints, existing research typically focuses on one of two scenarios: unstructured domains with many agents where we are content with heuristic solutions, or domains with small numbers of agents or special structure where we can provide provably near-optimal solutions. By contrast, in this paper, we focus on providing provably near-optimal solutions for domains with large numbers of agents, by exploiting a common domain-general property: if individual agents each have limited influence …

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Lagrangian Relaxation For Large-Scale Multi-Agent Planning, Geoff Gordon, Pradeep Reddy Varakantham, William Yeoh, Ajay Srinivasan, Hoong Chuin Lau, Shih-Fen Cheng May 2013

Lagrangian Relaxation For Large-Scale Multi-Agent Planning, Geoff Gordon, Pradeep Reddy Varakantham, William Yeoh, Ajay Srinivasan, Hoong Chuin Lau, Shih-Fen Cheng

Shih-Fen CHENG

Multi-agent planning is a well-studied problem with applications in various areas. Due to computational constraints, existing research typically focuses either on unstructured domains with many agents, where we are content with heuristic solutions, or domains with small numbers of agents or special structure, where we can find provably near-optimal solutions. In contrast, here we focus on provably near-optimal solutions in domains with many agents, by exploiting influence limits. To that end, we make two key contributions: (a) an algorithm, based on Lagrangian relaxation and randomized rounding, for solving multi-agent planning problems represented as large mixed-integer programs; (b) a proof of …

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Notes On Equilibria In Symmetric Games, Shih-Fen Cheng, Daniel M. Reeves, Yevgeniy Vorobeychik, Michael P. Wellman May 2013

Notes On Equilibria In Symmetric Games, Shih-Fen Cheng, Daniel M. Reeves, Yevgeniy Vorobeychik, Michael P. Wellman

Shih-Fen CHENG

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.

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Distributing Complementary Resources Across Multiple Periods With Stochastic Demand, Shih-Fen Cheng, John Tajan, Hoong Chuin Lau May 2013

Distributing Complementary Resources Across Multiple Periods With Stochastic Demand, Shih-Fen Cheng, John Tajan, Hoong Chuin Lau

Shih-Fen CHENG

In this paper, we evaluate whether the robustness of a market mechanism that allocates complementary resources could be improved through the aggregation of time periods in which resources are consumed. In particular, we study a multi-round combinatorial auction that is built on a general equilibrium framework. We adopt the general equilibrium framework and the particular combinatorial auction design from the literature, and we investigate the benefits and the limitation of time-period aggregation when demand-side uncertainties are introduced. By using simulation experiments, we show that under stochastic conditions the performance variation of the process decreases as the time frame length (time …

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Designing The Market Game For A Commodity Trading Simulation, Shih-Fen Cheng May 2013

Designing The Market Game For A Commodity Trading Simulation, Shih-Fen Cheng

Shih-Fen CHENG

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 …

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Would Price Limits Have Made Any Difference To The 'Flash Crash' On May 6, 2010, Wing Bernard Lee, Shih-Fen Cheng, Annie Koh May 2013

Would Price Limits Have Made Any Difference To The 'Flash Crash' On May 6, 2010, Wing Bernard Lee, Shih-Fen Cheng, Annie Koh

Shih-Fen CHENG

On May 6, 2010, the U.S. equity markets experienced a brief but highly unusual drop in prices across a number of stocks and indices. The Dow Jones Industrial Average (see Figure 1) fell by approximately 9% in a matter of minutes, and several stocks were traded down sharply before recovering a short time later. The authors contend that the events of May 6, 2010 exhibit patterns consistent with the type of "flash crash" observed in their earlier study (2010). This paper describes the results of nine different simulations created by using a large-scale computer model to reconstruct the critical elements …

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Decision Support For Assorted Populations In Uncertain And Congested Environments, Pradeep Reddy Varakantham, Asrar Ahmed, Shih-Fen Cheng May 2013

Decision Support For Assorted Populations In Uncertain And Congested Environments, Pradeep Reddy Varakantham, Asrar Ahmed, Shih-Fen Cheng

Shih-Fen Cheng

This research is motivated by large scale problems in urban transportation and labor mobility where there is congestion for resources and uncertainty in movement. In such domains, even though the individual agents do not have an identity of their own and do not explicitly interact with other agents, they effect other agents. While there has been much research in handling such implicit effects, it has primarily assumed deterministic movements of agents. We address the issue of decision support for individual agents that are identical and have involuntary movements in dynamic environments. For instance, in a taxi fleet serving a city, …

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An Analysis Of Extreme Price Shocks And Illiquidity Among Trend Followers, Bernard Lee, Shih-Fen Cheng, Annie Koh May 2013

An Analysis Of Extreme Price Shocks And Illiquidity Among Trend Followers, Bernard Lee, Shih-Fen Cheng, Annie Koh

Shih-Fen CHENG

We construct an agent-based model to study the interplay between extreme price shocks and illiquidity in the presence of systematic traders known as trend followers. The agent-based approach is particularly attractive in modeling commodity markets because the approach allows for the explicit modeling of production, capacities, and storage constraints. Our study begins by using the price stream from a market simulation involving human participants and studies the behavior of various trend-following strategies, assuming initially that their participation will not impact the market. We notice an incremental deterioration in strategy performance as and when strategies deviate further and further from the …

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A Mechanism For Organizing Last-Mile Service Using Non-Dedicated Fleet, Shih-Fen Cheng, Duc Thien Nguyen, Hoong Chuin Lau May 2013

A Mechanism For Organizing Last-Mile Service Using Non-Dedicated Fleet, Shih-Fen Cheng, Duc Thien Nguyen, Hoong Chuin Lau

Shih-Fen CHENG

Unprecedented pace of urbanization and rising income levels have fueled the growth of car ownership in almost all newly formed megacities. Such growth has congested the limited road space and significantly affected the quality of life in these megacities. Convincing residents to give up their cars and use public transport is the most effective way in reducing congestion; however, even with sufficient public transport capacity, the lack of last-mile (from the transport hub to the destination) travel services is the major deterrent for the adoption of public transport. Due to the dynamic nature of such travel demands, fixed-size fleets will …

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An Agent-Based Commodity Trading Simulation, Shih-Fen Cheng, Yee Pin Lim May 2013

An Agent-Based Commodity Trading Simulation, Shih-Fen Cheng, Yee Pin Lim

Shih-Fen CHENG

In this paper, an event-centric commodity trading simulation powered by the multiagent framework is presented. The purpose of this simulation platform is for training novice traders. The simulation is progressed by announcing news events that affect various aspects of the commodity supply chain. Upon receiving these events, market agents that play the roles of producers, consumers, and speculators would adjust their views on the market and act accordingly. Their actions would be based on their roles and also their private information, and collectively they shape the market dynamics. This simulation has been effectively deployed for several training sessions. We will …

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Iterated Weaker-Than-Weak Dominance, Shih-Fen Cheng, Michael P. Wellman May 2013

Iterated Weaker-Than-Weak Dominance, Shih-Fen Cheng, Michael P. Wellman

Shih-Fen CHENG

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 …

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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 May 2013

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

Shih-Fen CHENG

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 …

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Iterative Statistical Verification Of Probabilistic Plans, Colin M. Potts May 2013

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 …

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Modeling A Sensor To Improve Its Efficacy, Nabin K. Malakar, Daniil Gladkov, Kevin H. Knuth May 2013

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 …

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Desktop Warfare: Robotic Collaboration For Persistent Surveillance, Situational Awareness And Combat Operations, Jeremy Straub May 2013

Desktop Warfare: Robotic Collaboration For Persistent Surveillance, Situational Awareness And Combat Operations, Jeremy Straub

Jeremy Straub

Robotic sensing and weapons platforms can be controlled from a desktop workstation on the other side of the planet from where combat is occurring. This minimizes the potential for injury to soldiers and increases operational productivity. Significant work has been undertaken and is ongoing related to the autonomous control of battlefield sensing and warfighting systems. While many aspects of these operations can be performed autonomously, in some cases it is necessary (due to technical limitations) or desirable (due to legal or political implications) to involve humans in the low-level decision making. This paper reviews a number of specific applications where …

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A Review Of Online Collaboration Tools Used By The Und Openorbiter Program, Jeremy Straub, Christoffer Korvald May 2013

A Review Of Online Collaboration Tools Used By The Und Openorbiter Program, Jeremy Straub, Christoffer Korvald

Jeremy Straub

The OpenOrbiter program at the University of North Dakota is a student-initiated, student-run effort to design, develop, test, launch and operate a CubeSat-class spacecraft to validate the designs of the Open Prototype for Educational NanoSatellites (a framework that will be made publically-available to allow faster and lower-cost missions at other educational institutions worldwide). OpenOrbiter involves (at various participation levels) over 200 faculty and students spanning five colleges and ten departments. To coordinate this large group of participants who comprise over seventeen teams and work at disjoint hours in a plethora of locations, online project management, software source control and hardware …

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Spatial Computing In An Orbital Environment: An Exploration Of The Unique Constraints Of This Special Case To Other Spatial Computing Environments, Jeremy Straub May 2013

Spatial Computing In An Orbital Environment: An Exploration Of The Unique Constraints Of This Special Case To Other Spatial Computing Environments, Jeremy Straub

Jeremy Straub

The creation of an orbital services model (where spacecraft expose their capabilities for use by other spacecraft as part of a service-for-hire or barter system) requires effective determination of how to best transmit information between the two collaborating spacecraft. Existing approaches developed for ad hoc networking (e.g., wireless networks with users entering and departing in a pseudo-random fashion) exist; however, these fail to generate optimal solutions as they ignore a critical piece of available information. This additional piece of information is the orbital characteristics of the spacecraft. A spacecraft’s orbit is nearly deterministic if the magnitude and direction of its …

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Practical Tractability Of Csps By Higher Level Consistency And Tree Decomposition, Shant Karakashian May 2013

Practical Tractability Of Csps By Higher Level Consistency And Tree Decomposition, Shant Karakashian

Department of Computer Science and Engineering: 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: …

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Master Physician Scheduling Problem, Aldy Gunawan, Hoong Chuin Lau May 2013

Master Physician Scheduling Problem, Aldy Gunawan, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

We study a real-world problem arising from the operations of a hospital service provider, which we term the master physician scheduling problem. It is a planning problem of assigning physicians’ full range of day-to-day duties (including surgery, clinics, scopes, calls, administration) to the defined time slots/shifts over a time horizon, incorporating a large number of constraints and complex physician preferences. The goals are to satisfy as many physicians’ preferences and duty requirements as possible while ensuring optimum usage of available resources. We propose mathematical programming models that represent different variants of this problem. The models were tested on a real …

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Implementation Of Slowly Changing Dimension To Data Warehouse To Manage Marketing Campaigns In Banks, Lihui Wang, Junyu Choy, Michelle L. F. Cheong May 2013

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 …

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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 May 2013

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 …

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Distributed Gibbs: A Memory-Bounded Sampling-Based Dcop Algorithm, Duc Thien Nguyen, William Yeoh, Hoong Chuin Lau May 2013

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 …

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Tesla: An Energy-Saving Agent That Leverages Schedule Flexibility, Jun Young Kwak, Pradeep Varakantham, Rajiv Maheswaran, Burcin Becerik-Gerber, Milind Tambe May 2013

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 …

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Anonymous Authentication Of Visitors For Mobile Crowd Sensing At Amusement Parks, Divyan Konidala, Robert H. Deng, Yingjiu Li, Hoong Chuin Lau, Stephen Fienberg May 2013

Anonymous Authentication Of Visitors For Mobile Crowd Sensing At Amusement Parks, Divyan Konidala, Robert H. Deng, Yingjiu Li, Hoong Chuin Lau, Stephen Fienberg

Research Collection School Of Computing and Information Systems

In this paper we focus on authentication and privacy aspects of an application scenario that utilizes mobile crowd sensing for the benefit of amusement park operators and their visitors. The scenario involves a mobile app that gathers visitors’ demographic details, preferences, and current location coordinates, and sends them to the park’s sever for various analyses. These analyses assist the park operators to efficiently deploy their resources, estimate waiting times and queue lengths, and understand the behavior of individual visitors and groups. The app server also offers visitors optimal recommendations on routes and attractions for an improved dynamic experience and minimized …

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Traditional Media Seen From Social Media, Jisun An, Daniele Quercia, Meeyoung Cha, Krishna Gummadi, Jon Crowcroft May 2013

Traditional Media Seen From Social Media, Jisun An, Daniele Quercia, Meeyoung Cha, Krishna Gummadi, Jon Crowcroft

Research Collection School Of Computing and Information Systems

With the advent of social media services, media outlets have started reaching audiences on social-networking sites. On Twitter, users actively follow a wide set of media sources, form interpersonal networks, and propagate interesting stories to their peers. These media subscription and interaction patterns, which had previously been hidden behind media corporations' databases, offer new opportunities to understand media supply and demand on a large scale. Through a map that connects 77 media outlets based on Twitter subscription patterns, we are able to answer a variety of questions: to what extent New York Times and the Wall Street Journal readers overlap? …

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Hybrid Methods For Feature Selection, Iunniang Cheng May 2013

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 …

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Context-Driven Image Annotation Using Imagenet, George E. Noel, Gilbert L. Peterson May 2013

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 …

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Enhancing Robot Perception Using Human Teammates, Jean Oh, Arne Suppe, Anthony Stentz, Martial Hebert May 2013

Enhancing Robot Perception Using Human Teammates, Jean Oh, Arne Suppe, Anthony Stentz, Martial Hebert

Research Collection School Of Computing and Information Systems

In robotics research, perception is one of the most challenging tasks. In contrast to existing approaches that rely only on computer vision, we propose an alternative method for improving perception by learning from human teammates. To evaluate, we apply this idea to a door detection problem. A set of preliminary experiments has been completed using software agents with real vision data. Our results demonstrate that information inferred from teammate observations significantly improves the perception precision.

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Why Individuals Seek Diverse Opinions (Or Why They Don't), Jisun An, Daniele Quercia, Jon Crowcroft May 2013

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 …

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Roulette Wheel Selection Game Player, Scott Tong May 2013

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 …

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