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Articles 7591 - 7620 of 10550
Full-Text Articles in Entire DC Network
Parameter Learning For Latent Network Diffusion, Xiaojian Wu, Akshat Kumar, Daniel Sheldon, Shlomo Zilberstein
Parameter Learning For Latent Network Diffusion, Xiaojian Wu, Akshat Kumar, Daniel Sheldon, Shlomo Zilberstein
Research Collection School Of Computing and Information Systems
Diffusion processes in networks are increasingly used to model dynamic phenomena such as the spread of information, wildlife, or social influence. Our work addresses the problem of learning the underlying parameters that govern such a diffusion process by observing the time at which nodes become active. A key advantage of our approach is that, unlike previous work, it can tolerate missing observations for some nodes in the diffusion process. Having incomplete observations is characteristic of offline networks used to model the spread of wildlife. We develop an EM algorithm to address parameter learning in such settings. Since both the E …
Near-Duplicate Video Retrieval: Current Research And Future Trends, Jiajun Liu, Zi Huang, Hongyun Cai, Heng Tao Shen, Chong-Wah Ngo, Wei Wang
Near-Duplicate Video Retrieval: Current Research And Future Trends, Jiajun Liu, Zi Huang, Hongyun Cai, Heng Tao Shen, Chong-Wah Ngo, Wei Wang
Research Collection School Of Computing and Information Systems
The exponential growth of online videos, along with increasing user involvement in video-related activities, has been observed as a constant phenomenon during the last decade. User's time spent on video capturing, editing, uploading, searching, and viewing has boosted to an unprecedented level. The massive publishing and sharing of videos has given rise to the existence of an already large amount of near-duplicate content. This imposes urgent demands on near-duplicate video retrieval as a key role in novel tasks such as video search, video copyright protection, video recommendation, and many more. Driven by its significance, near-duplicate video retrieval has recently attracted …
Click-Boosting Random Walk For Image Search Reranking, Xiaopeng Yang, Yongdong Zhang, Ting Yao, Zheng-Jun Zha, Chong-Wah Ngo
Click-Boosting Random Walk For Image Search Reranking, Xiaopeng Yang, Yongdong Zhang, Ting Yao, Zheng-Jun Zha, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Image reranking is an effective way for improving the retrieval performance of keyword-based image search engines. A fundamental issue underlying the success of existing image reranking approaches is the ability in identifying potentially useful recurrent patterns or relevant training examples from the initial search results. Ideally, these patterns and examples can be leveraged to upgrade the ranks of visually similar images, which are also likely to be relevant. The challenge, nevertheless, originates from the fact that keyword-based queries are used to be ambiguous, resulting in difficulty in predicting the search intention. Mining useful patterns and examples without understanding query is …
Self-Organizing Cognitive Models For Virtual Agents, Yilin Kang, Ah-Hwee Tan
Self-Organizing Cognitive Models For Virtual Agents, Yilin Kang, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
Three key requirements of realistic characters or agents in virtual world can be identified as autonomy, interactivity, and personification. Working towards these challenges, this paper proposes a brain inspired agent architecture that integrates goal-directed autonomy, natural language interaction and human-like personification. Based on self-organizing neural models, the agent architecture maintains explicit mental representation of desires, intention, personalities, self-awareness, situation awareness and user awareness. Autonomous behaviors are generated via evaluating the current situation with active goals and learning the most appropriate social or goal-directed rule from the available knowledge, in accordance with the personality of each individual agent. We have built …
Open Source Software Development Process Model – A Grounded Theory Approach, Keng Siau, Y. Tian
Open Source Software Development Process Model – A Grounded Theory Approach, Keng Siau, Y. Tian
Research Collection School Of Computing and Information Systems
The open source movement has provided software users with more choices, lower software acquisition cost, more flexible software customization, and possibly higher quality software product. Although the development of open source software is dynamic and it encourages innovations, the process can be chaotic. An Open Source Software Development (OSSD) process model to enhance the survivability of OSSD projects is needed. This research uses the grounded theory approach to derive a Phase-Role-Skill-Responsibility (PRSR) OSSD process model. The three OSSD process phases -- Launch Stage, Before the First Release, and Between Releases -- address the characteristics of the OSSD process as well …
Riskvis: Supply Chain Visualization With Risk Management And Real-Time Monitoring, Rick S. M. Goh, Zhaoxia Wang, Xiaofeng Yin, Xiuju Fu, Loganathan Ponnanbalam, Sifei Lu, Xiaorong Li
Riskvis: Supply Chain Visualization With Risk Management And Real-Time Monitoring, Rick S. M. Goh, Zhaoxia Wang, Xiaofeng Yin, Xiuju Fu, Loganathan Ponnanbalam, Sifei Lu, Xiaorong Li
Research Collection School Of Computing and Information Systems
With increased complexity, supply chain networks (SCNs) of modern era face higher risks and lower efficiency due to limited visibility. Hence, there is an immediate need to provide end-to-end supply chain visibility for efficient management of complex supply chains. This paper proposes a visualization scheme based on multi-hierarchical modular design and develops a supply chain visualization platform with risk management and real-time monitoring, named RiskVis, for realizing better Supply Chain Risk Management (SCRM). A Supply Chain Visualizer (SCV) with a graphical visualization platform is mounted as a part of a SCRM management decision-making dashboard and it provides senior management a …
Vigilance Adaptation In Adaptive Resonance Theory, Lei Meng, Ah-Hwee Tan, Donald C. Winsch
Vigilance Adaptation In Adaptive Resonance Theory, Lei Meng, Ah-Hwee Tan, Donald C. Winsch
Research Collection School Of Computing and Information Systems
Despite the advantages of fast and stable learning, Adaptive Resonance Theory (ART) still relies on an empirically fixed vigilance parameter value to determine the vigilance regions of all of the clusters in the category field (F 2 ), causing its performance to depend on the vigilance value. It would be desirable to use different values of vigilance for different category field nodes, in order to fit the data with a smaller number of categories. We therefore introduce two methods, the Activation Maximization Rule (AMR) and the Confliction Minimization Rule (CMR). Despite their differences, both ART with AMR (AM-ART) and with …
An Agent-Based Network Analytic Perspective On The Evolution Of Complex Adaptive Supply Chain Networks, L. Ponnambalam, A. Tan, X. Fu, X. F. Yin, Zhaoxia Wang, R. S. Goh
An Agent-Based Network Analytic Perspective On The Evolution Of Complex Adaptive Supply Chain Networks, L. Ponnambalam, A. Tan, X. Fu, X. F. Yin, Zhaoxia Wang, R. S. Goh
Research Collection School Of Computing and Information Systems
Supply chain networks of modern era are complex adaptive systems that are dynamic and highly interdependent in nature. Business continuity of these complex systems depend vastly on understanding as to how the supply chain network evolves over time (based on the policies it adapts), and identifying the susceptibility of the evolved networks to external disruptions. The objective of this article is to illustrate as to how an agent-based network analytic perspective can aid this understanding on the network-evolution dynamics, and identification of disruption effects on the evolved networks. To this end, we developed a 4-tier agent based supply chain model …
Improving Traffic Prediction With Tweet Semantics, Jingrui He, Wei Shen, Phani Divakaruni, Laura Wynter, Rick Lawrence
Improving Traffic Prediction With Tweet Semantics, Jingrui He, Wei Shen, Phani Divakaruni, Laura Wynter, Rick Lawrence
Research Collection School Of Computing and Information Systems
Road traffic prediction is a critical component in modern smart transportation systems. It provides the basis for traffic management agencies to generate proactive traffic operation strategies for alleviating congestion. Existing work on near-term traffic prediction (forecasting horizons in the range of 5 minutes to 1 hour) relies on the past and current traffic conditions. However, once the forecasting horizon is beyond 1 hour, i.e., in longer-term traffic prediction, these techniques do not work well since additional factors other than the past and current traffic conditions start to play important roles.To address this problem, in this paper, for the first time, …
Cost-Sensitive Online Active Learning With Application To Malicious Url Detection, Peilin Zhao, Steven C. H. Hoi
Cost-Sensitive Online Active Learning With Application To Malicious Url Detection, Peilin Zhao, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
Malicious Uniform Resource Locator (URL) detection is an important problem in web search and mining, which plays a critical role in internet security. In literature, many existing studies have attempted to formulate the problem as a regular supervised binary classification task, which typically aims to optimize the prediction accuracy. However, in a real-world malicious URL detection task, the ratio between the number of malicious URLs and legitimate URLs is highly imbalanced, making it very inappropriate for simply optimizing the prediction accuracy. Besides, another key limitation of the existing work is to assume a large amount of training data is available, …
Large Scale Online Kernel Classification, Jialei Wang, Peilin Zhao, Steven C. H. Hoi, Jinfeng Zhuang, Zhi-Yong Liu
Large Scale Online Kernel Classification, Jialei Wang, Peilin Zhao, Steven C. H. Hoi, Jinfeng Zhuang, Zhi-Yong Liu
Research Collection School Of Computing and Information Systems
In this work, we present a new framework for large scale online kernel classification, making kernel methods efficient and scalable for large-scale online learning tasks. Unlike the regular budget kernel online learning scheme that usually uses different strategies to bound the number of support vectors, our framework explores a functional approximation approach to approximating a kernel function/matrix in order to make the subsequent online learning task efficient and scalable. Specifically, we present two different online kernel machine learning algorithms: (i) the Fourier Online Gradient Descent (FOGD) algorithm that applies the random Fourier features for approximating kernel functions; and (ii) the …
Learning To Name Faces: A Multimodal Learning Scheme For Search-Based Face Annotation, Dayong Wang, Steven C. H. Hoi, Pengcheng Wu, Jianke Zhu, Ying He, Chunyan Miao
Learning To Name Faces: A Multimodal Learning Scheme For Search-Based Face Annotation, Dayong Wang, Steven C. H. Hoi, Pengcheng Wu, Jianke Zhu, Ying He, Chunyan Miao
Research Collection School Of Computing and Information Systems
Automated face annotation aims to automatically detect human faces from a photo and further name the faces with the corresponding human names. In this paper, we tackle this open problem by investigating a search-based face annotation (SBFA) paradigm for mining large amounts of web facial images freely available on the WWW. Given a query facial image for annotation, the idea of SBFA is to first search for top-n similar facial images from a web facial image database and then exploit these top-ranked similar facial images and their weak labels for naming the query facial image. To fully mine those information, …
Performance Measurement Design For A Parcel Delivery Company, Junyu Choy, Nang Laik Ma, Ping Shung Koo
Performance Measurement Design For A Parcel Delivery Company, Junyu Choy, Nang Laik Ma, Ping Shung Koo
Research Collection School Of Computing and Information Systems
There were extensive researches on the topic of performance management in various organizations across multiple fields. Literature on performance measurements in logistics can be divided into specific measures and their application in the context or complete framework for performance measurements. In this paper, the focus of the discussion will be the formulation of the framework which handles performance measurements for package delivery service and how the metrics measure the performance and their application in the context of package delivery service.
Real-Life Vehicle Routing With Non-Standard Constraints, Wee Leong Lee
Real-Life Vehicle Routing With Non-Standard Constraints, Wee Leong Lee
Research Collection School Of Computing and Information Systems
Real-life vehicle routing problems comprise of a number of complexities that are not considered by the classical models found in vehicle routing literature. I present, in this paper, a two-stage sweep-based heuristic to find good solutions to a real-life Vehicle Routing Problem (VRP). The problem I shall consider, will deal with some non-standard constraints beyond those normally associated with the classical VRP. Other than considering the capacity constraints for vehicles and the time windows for deliveries, I shall introduce four additional non-standard constraints: merging of customer orders, controlling the maximum number of drop points, matching orders to vehicle types, and …
Usability Of Performance Dashboards, Usefulness Of Operational And Tactical Support, And Quality Of Strategic Support: A Research Framework, Bih-Ru Lea, Fiona Fui-Hoon Nah
Usability Of Performance Dashboards, Usefulness Of Operational And Tactical Support, And Quality Of Strategic Support: A Research Framework, Bih-Ru Lea, Fiona Fui-Hoon Nah
Research Collection School Of Computing and Information Systems
Performance dashboards are used as a strategic decision support tool in organizations. In this research, we examine the relationships between the usability of performance dashboards, the usefulness of operational and tactical support, and the quality of strategic support that they provide. We hypothesize that usability of performance dashboards will influence user perceptions of the usefulness of the operational and tactical support provided by the dashboards, which in turn influence the perceived quality of strategic support provided.
Technique For Authenticating H.264/Svc Streams In Surveillance Applications, Wei Zhuo, Robert H. Deng, Jialie Shen, Yongdong Wu, Xuhua Ding, Swee Won Lo
Technique For Authenticating H.264/Svc Streams In Surveillance Applications, Wei Zhuo, Robert H. Deng, Jialie Shen, Yongdong Wu, Xuhua Ding, Swee Won Lo
Research Collection School Of Computing and Information Systems
Surveillance codestreams coded by H.264/SVC (scalable video coding), which consists of one base layer and one or more enhancement layers, supply flexible and various quality, resolution, and temporal (sub)codestreams such that clients with different network bandwidth and terminal devices can seamlessly access them. In this paper, we present a robust authentication scheme for them in order to insure the integrity of SVC surveillance codestreams, named AUSSC (Authenticating SVC Surveillance Codestreams). AUSSC exploits cryptographic-based authentication for base layer and content-based authentication for enhancement layers. For content-based authentication, AUSSC extracts full features from the first frame of each GOP (group of picture) …
An Empirical Study Of Bugs In Software Build Systems, Xin Xia, Xiaozhen Zhou, David Lo, Xiaoqiong Zhao
An Empirical Study Of Bugs In Software Build Systems, Xin Xia, Xiaozhen Zhou, David Lo, Xiaoqiong Zhao
Research Collection School Of Computing and Information Systems
Build system converts source code, libraries and other data into executable programs by orchestrating the execution of compilers and other tools. The whole building process is managed by a software build system, such as Make, Ant, CMake, Maven, Scons, and QMake. The reliability of software build systems would affect the reliability of the build process. In this paper, we perform an empirical study on bugs in software build systems. We analyze four software build systems, Ant, Maven, CMake and QMake, which are four typical and widely-used software build systems, and can be used to build Java, C, C++ systems. We …
Active Learning With Expert Advice, Peilin Zhao, Steven C. H. Hoi, Jinfeng Zhuang
Active Learning With Expert Advice, Peilin Zhao, Steven C. H. Hoi, Jinfeng Zhuang
Research Collection School Of Computing and Information Systems
Conventional learning with expert advice methods assumes a learner is always receiving the outcome (e.g., class labels) of every incoming training instance at the end of each trial. In real applications, acquiring the outcome from oracle can be costly or time consuming. In this paper, we address a new problem of active learning with expert advice, where the outcome of an instance is disclosed only when it is requested by the online learner. Our goal is to learn an accurate prediction model by asking the oracle the number of questions as small as possible. To address this challenge, we propose …
Allocative Efficiency, Mark-Ups, And The Welfare Gains From Trade, Thomas J. Holmes, Wen-Tai Hsu, Sanghoon Lee
Allocative Efficiency, Mark-Ups, And The Welfare Gains From Trade, Thomas J. Holmes, Wen-Tai Hsu, Sanghoon Lee
Research Collection School Of Economics
This paper develops an index of allocative efficiency that depends upon the distribution of mark-ups across goods and is separable from an index of standard Ricardian gains from trade. It determines how changes in trade frictions affect allocative efficiency in an oligopoly model of international trade, decomposing the effect into the cost-change channel and the price-change channel. Formulas are derived shedding light on the signs and magnitudes of the two channels. In symmetric country models, trade tends to increase allocative efficiency through the cost-change channel, yielding a welfare benefit beyond productive efficiency gains. In contrast, the price-change channel has ambiguous …
Psyhcos: Parameter Synthesis For Hierarchical Concurrent Real-Time Systems, Étienne André, Yang Liu, Jun Sun, Jin Song Dong, Shang-Wei Lin
Psyhcos: Parameter Synthesis For Hierarchical Concurrent Real-Time Systems, Étienne André, Yang Liu, Jun Sun, Jin Song Dong, Shang-Wei Lin
Research Collection School Of Computing and Information Systems
Real-time systems are often hard to control, due to their complicated structures, quantitative time factors and even unknown delays. We present here PSyHCoS, a tool for analyzing parametric real-time systems specified using the hierarchical modeling language PSTCSP. PSyHCoS supports several algorithms for parameter synthesis and model checking, as well as state space reduction techniques. Its architecture favors reusability in terms of syntax, semantics, and algorithms. It comes with a friendly user interface that can be used to edit, simulate and verify PSTCSP models. Experiments show its efficiency and applicability
Combining Model Checking And Testing With An Application To Reliability Prediction And Distribution, Lin Gui, Jun Sun, Yang Liu, Yuanjie Si, Jin Song Dong, Xinyu Wang
Combining Model Checking And Testing With An Application To Reliability Prediction And Distribution, Lin Gui, Jun Sun, Yang Liu, Yuanjie Si, Jin Song Dong, Xinyu Wang
Research Collection School Of Computing and Information Systems
Testing provides a probabilistic assurance of system correctness. In general, testing relies on the assumptions that the system under test is deterministic so that test cases can be sampled. However, a challenge arises when a system under test behaves non-deterministiclly in a dynamic operating environment because it will be unknown how to sample test cases.In this work, we propose a method combining hypothesis testing and probabilistic model checking so as to provide the ``assurance" and quantify the error bounds. The idea is to apply hypothesis testing to deterministic system components and use probabilistic model checking techniques to lift the results …
Evaluations Of Port Performances From A Seaborne Cargo Supply Chain Perspective, Joyce M. W. Low, Shao Wei Lam, Loon Ching Tang, Zhang Lan
Evaluations Of Port Performances From A Seaborne Cargo Supply Chain Perspective, Joyce M. W. Low, Shao Wei Lam, Loon Ching Tang, Zhang Lan
Research Collection Lee Kong Chian School Of Business
Previous research on port efficiency focuses primarily on the provider’s perspective and assumes that maximizing the output is always desirable. This paper recognizes that maximizing the final output does not necessarily guarantee an efficient system and the notion of port efficiency and service effectiveness needs to be considered from the perspectives of both the provider and the consumer of the port service. The paper proposes a network-DEA model to evaluate the performances of 30 seaports worldwide. The concurrent consideration of efficiency scores from the network-DEA model and the traditional DEA-CCR model will offer valuable insights to port operators on how …
Mining Direct Antagonistic Communities In Signed Social Networks, David Lo, Didi Surian, Philips Kokoh Prasetyo, Zhang Kuan, Ee Peng Lim
Mining Direct Antagonistic Communities In Signed Social Networks, David Lo, Didi Surian, Philips Kokoh Prasetyo, Zhang Kuan, Ee Peng Lim
Research Collection School Of Computing and Information Systems
Social networks provide a wealth of data to study relationship dynamics among people. Most social networks such as Epinions and Facebook allow users to declare trusts or friendships with other users. Some of them also allow users to declare distrusts or negative relationships. When both positive and negative links co-exist in a network, some interesting community structures can be studied. In this work, we mine Direct Antagonistic Communities (DACs) within such signed networks. Each DAC consists of two sub-communities with positive relationships among members of each sub-community, and negative relationships among members of the other sub-community. Identifying direct antagonistic communities …
Using Case Studies To Design And Deliver Technology-Centered Computing Education Courses: An Innovative Approach From An Undergraduate Information Systems Program In Singapore, Ilse Baumgartner
Research Collection School Of Computing and Information Systems
While the advantages of using case studies as an educational vehicle in computing education appear to be more than obvious, there is a very limited amount of research works or practice papers reporting on actual implementations of undergraduate or graduate computing courses which would be largely based on case studies. This conference contribution reports on selected best practices of course design and delivery implemented in one of the core courses of the Bachelor of Science (Information Systems Management) degree program (BSc (ISM)) offered by the School of Information Systems (SIS) at the Singapore Management University (SMU). Nearly all assessments, exercises, …
Shortlisting Top-K Assignments, Yimin Lin, Kyriakos Mouratidis
Shortlisting Top-K Assignments, Yimin Lin, Kyriakos Mouratidis
Research Collection School Of Computing and Information Systems
In this paper we identify a novel query type, the top-K assignment query (αTop-K). Consider a set of objects and a set of suppliers, where each object must be assigned to one supplier. Assume that there is a cost associated with every object-supplier pair. If we allocate each object to the server with the smallest cost (for the specific object), the derived overall assignment will have the minimum total cost. In many scenarios, however, runner-up assignments may be required too, like for example when a decision maker needs to make additional considerations, not captured by individual object-supplier costs. In this …
Orion: A Software Project Search Engine With Integrated Diverse Software Artifacts, Tegawende F. Bissyande, Ferdian Thung, David Lo, Lingxiao Jiang, Laurent Réveillère
Orion: A Software Project Search Engine With Integrated Diverse Software Artifacts, Tegawende F. Bissyande, Ferdian Thung, David Lo, Lingxiao Jiang, Laurent Réveillère
Research Collection School Of Computing and Information Systems
Software projects produce a wealth of data that is leveraged in different tasks and for different purposes: researchers collect project data for building experimental datasets; software programmers reuse code from projects; developers often explore the opportunities for getting involved in the development of a project to gain or offer expertise. Finding relevant projects that suit one needs is however currently challenging with the capabilities of existing search systems. We propose Orion, an integrated search engine architecture that combines information from different types of software repositories from multiple sources to facilitate the construction and execution of advanced search queries. Orion provides …
Popularity, Interoperability, And Impact Of Programming Languages In 100,000 Open Source Projects, Tegawende F. Bissyande, Ferdian Thung, David Lo, Lingxiao Jiang, Laurent Réveillère
Popularity, Interoperability, And Impact Of Programming Languages In 100,000 Open Source Projects, Tegawende F. Bissyande, Ferdian Thung, David Lo, Lingxiao Jiang, Laurent Réveillère
Research Collection School Of Computing and Information Systems
Programming languages have been proposed even before the era of the modern computer. As years have gone, computer resources have increased and application domains have expanded, leading to the proliferation of hundreds of programming languages, each attempting to improve over others or to address new programming paradigms. These languages range from procedural languages like C, object oriented languages like Java, and functional languages such as ML and Haskell. Unfortunately, there is a lack of large scale and comprehensive studies that examine the “popularity”, “interoperability”, and “impact” of various programming languages. To fill this gap, this study investigates a hundred thousands …
Reviving Dormant Ties In An Online Social Network Experiment, Ee Peng Lim, Denzil Correa, David Lo, Michael Finegold, Feida Zhu
Reviving Dormant Ties In An Online Social Network Experiment, Ee Peng Lim, Denzil Correa, David Lo, Michael Finegold, Feida Zhu
Research Collection School Of Computing and Information Systems
Social network users connect and interact with one another to fulfil different kinds of social and information needs. When interaction ceases between two users, we say that their tie becomes dormant. While there are different underlying reasons of dormant ties, it is important to find means to revive such ties so as to maintain vibrancy in the relationships. In this work, we thus focus on designing an online experiment to evaluate the effectiveness of personalized social messages to revive dormant ties. The experiment carefully selects users with dormant ties so that no user gets mixed treatments and be affected by …
The Case For Mobile Forensics Of Private Data Leaks: Towards Large-Scale User-Oriented Privacy Protection, Joseph Joo Keng Chan, Kiat Wee Tan, Lingxiao Jiang, Rajesh Krishna Balan
The Case For Mobile Forensics Of Private Data Leaks: Towards Large-Scale User-Oriented Privacy Protection, Joseph Joo Keng Chan, Kiat Wee Tan, Lingxiao Jiang, Rajesh Krishna Balan
Research Collection School Of Computing and Information Systems
Privacy protection against mobile applications on mobile devices is becoming a serious concern as user sensitive data may be leaked without proper justification. Most current leak detection tools only report leaked private data, but provide inadequate information about the causes of the leaks for end users to take preventive measures. Hence, users often cannot reconcile the way they have used an application to a reported leak — i.e., they are unable to comprehend the (il)legitimacy of the leak or make a decision on whether to allow the leak. This paper aims to demonstrate the feasibility and benefits of identifying the …
The Evolution Of Modular Product Architectures And The Emergence Of Platform Ecosystems, C. Jason Woodard, Eric K. Clemons
The Evolution Of Modular Product Architectures And The Emergence Of Platform Ecosystems, C. Jason Woodard, Eric K. Clemons
Research Collection School Of Computing and Information Systems
While a large body of research has examined the advantages and disadvantages of modularity in product design, studies of modularization have tended to focus on settings in which a product’s architecture is determined by a single designer or designers within a single organization. In this paper, we ask whether modularity can arise in a decentralized setting where high-value designs are rewarded but designers’ ability to coordinate with each other and anticipate the consequences of their actions is limited—in short, whether modularity can evolve. To answer this question, we developed an agent-based model in which boundedly rational firms combine components into …