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Articles 1 - 21 of 21
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A Fuzzy Logic Controller For Autonomous Wheeled Vehicles, Mohamed Trabia, Linda Z. Shi, Neil Eugene Hodge
A Fuzzy Logic Controller For Autonomous Wheeled Vehicles, Mohamed Trabia, Linda Z. Shi, Neil Eugene Hodge
Mechanical Engineering Faculty Research
Autonomous vehicles have potential applications in many fields, such as replacing humans in hazardous environments, conducting military missions, and performing routine tasks for industry. Driving ground vehicles is an area where human performance has proven to be reliable. Drivers typically respond quickly to sudden changes in their environment. While other control techniques may be used to control a vehicle, fuzzy logic has certain advantages in this area; one of them is its ability to incorporate human knowledge and experience, via language, into relationships among the given quantities. Fuzzy logic controllers for autonomous vehicles have been successfully applied to address various …
Cosign: A Parallel Algorithm For Coordinated Traffic Signal Control, Shih-Fen Cheng, Marina A. Epelman, Robert L. Smith
Cosign: A Parallel Algorithm For Coordinated Traffic Signal Control, Shih-Fen Cheng, Marina A. Epelman, Robert L. Smith
Research Collection School Of Computing and Information Systems
The problem of finding optimal coordinated signal timing plans for a large number of traffic signals is a challenging problem because of the exponential growth in the number of joint timing plans that need to be explored as the network size grows. In this paper, the game-theoretic paradigm of fictitious play to iteratively search for a coordinated signal timing plan is employed, which improves a system-wide performance criterion for a traffic network. The algorithm is robustly scalable to realistic-size networks modeled with high-fidelity simulations. Results of a case study for the city of Troy, MI, where there are 75 signalized …
Dynamic Multi-Linked Negotiations In Multi-Echelon Production Scheduling Networks, Hoong Chuin Lau, Guan Li Soh, Wee Chong Wan
Dynamic Multi-Linked Negotiations In Multi-Echelon Production Scheduling Networks, Hoong Chuin Lau, Guan Li Soh, Wee Chong Wan
Research Collection School Of Computing and Information Systems
In this paper, we are concerned with scheduling resources in a multi-tier production/logistics system for multi-indenture goods. Unlike classical production scheduling problems, the problem we study is concerned with local utilities which are private. We present an agent model and investigate an efficient scheme for handling multi-linked agent negotiations. With this scheme we attempt to overcome the drawbacks of sequential negotiations and negotiation parameter settings. Our approach is based on embedding a credit-based negotiation protocol within a local search scheduling algorithm. We demonstrate the computational efficiency and effectiveness of the approach in solving a real-life dynamic production scheduling problem which …
Plans As Products Of Learning, Samin Karim, Budhitama Subagdja, Liz Sonenberg
Plans As Products Of Learning, Samin Karim, Budhitama Subagdja, Liz Sonenberg
Research Collection School Of Computing and Information Systems
This paper presents motivations and current related work in the field of plan learning. Additionally, two approaches that achieve plan learning are presented. The two presented approaches are centred on the BDI framework of agency and have particular focus on plans, which, alongside goals, are the means to fulfil intentions in most pragmatic and theoretical realisations of the BDI framework. The first approach is a hybrid architecture that combines a BDI plan extractor and executor with a generic low-level learner. The second approach uses hypotheses to suggest incremental refinements of a priori plans. Both approaches achieve plan generation that is …
Robust Controllability In Temporal Constraint Networks Under Uncertainty, Hoong Chuin Lau, Jia Li, Roland H. C. Yap
Robust Controllability In Temporal Constraint Networks Under Uncertainty, Hoong Chuin Lau, Jia Li, Roland H. C. Yap
Research Collection School Of Computing and Information Systems
Temporal constraint networks are embedded in many planning and scheduling problems. In dynamic problems, a fundamental challenge is to decide whether such a network can be executed as uncertainty is revealed over time. Very little work in this domain has been done in the probabilistic context. In this paper, we propose a Temporal Constraint Network (TCN) model where durations of uncertain activities are represented by random variables. We wish to know whether such a network is robust controllable, i.e. can be executed dynamically within a given failure probability, and if so, how one might find a feasible schedule as the …
Pedagogical Possibilities For The N-Puzzle Problem, Zdravko Markov, Ingrid Russell, Todd W. Neller, Neli Zlatareva
Pedagogical Possibilities For The N-Puzzle Problem, Zdravko Markov, Ingrid Russell, Todd W. Neller, Neli Zlatareva
Computer Science Faculty Publications
In this paper we present work on a project funded by the National Science Foundation with a goal of unifying the Artificial Intelligence (AI) course around the theme of machine learning. Our work involves the development and testing of an adaptable framework for the presentation of core AI topics that emphasizes the relationship between AI and computer science. Several hands-on laboratory projects that can be closely integrated into an introductory AI course have been developed. We present an overview of one of the projects and describe the associated curricular materials that have been developed. The project uses machine learning as …
Two-Instant Reallocation In Two-Echelon Spare Parts Inventory Systems, Huawei Song, Hoong Chuin Lau
Two-Instant Reallocation In Two-Echelon Spare Parts Inventory Systems, Huawei Song, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
In this paper, we study the problem of deciding when and how to perform reallocation of existing spare parts in a multi-echelon reparable item inventory system. We present a mathematical model that solves the problem when there are two reallocation instants, in response to the open challenge post by Cao and Silver(2005) to consider two or more possible reallocations within a replenishment cycle.
Viz: A Visual Analysis Suite For Explaining Local Search Behavior, Steven Halim, Roland H. C. Yap, Hoong Chuin Lau
Viz: A Visual Analysis Suite For Explaining Local Search Behavior, Steven Halim, Roland H. C. Yap, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
NP-hard combinatorial optimization problems are common in real life. Due to their intractability, local search algorithms are often used to solve such problems. Since these algorithms are heuristic-based, it is hard to understand how to improve or tune them. We propose an interactive visualization tool, VIZ, meant for understanding the behavior of local search. VIZ uses animation of abstract search trajectories with other visualizations which are also animated in a VCR-like fashion to graphically playback the algorithm behavior. It combines generic visualizations applicable on arbitrary algorithms with algorithm and problem specific visualizations. We use a variety of techniques such as …
Fuzzy Cognitive Goal Net For Interactive Storytelling Plot Design, Yundong Cai, Chunyan Miao, Ah-Hwee Tan, Zhiqi Shen
Fuzzy Cognitive Goal Net For Interactive Storytelling Plot Design, Yundong Cai, Chunyan Miao, Ah-Hwee Tan, Zhiqi Shen
Research Collection School Of Computing and Information Systems
Interactive storytelling attracts a lot of research interests among the interactive entertainments in recent years. Designing story plot for interactive storytelling is currently one of the most critical problems of interactive storytelling. Some traditional AI planning methods, such as Hierarchical Task Network, Heuristic Searching Method are widely used as the planning tool for the story plot design. This paper proposes a model called Fuzzy Cognitive Goal Net as the story plot planning tool for interactive storytelling, which combines the planning capability of Goal net and reasoning ability of Fuzzy Cognitive Maps. Compared to conventional methods, the proposed model shows a …
Fuzzy State Aggregation And Off-Policy Reinforcement Learning For Stochastic Environments, Dean C. Wardell, Gilbert L. Peterson
Fuzzy State Aggregation And Off-Policy Reinforcement Learning For Stochastic Environments, Dean C. Wardell, Gilbert L. Peterson
Faculty Publications
Reinforcement learning is one of the more attractive machine learning technologies, due to its unsupervised learning structure and ability to continually learn even as the environment it is operating in changes. This ability to learn in an unsupervised manner in a changing environment is applicable in complex domains through the use of function approximation of the domain’s policy. The function approximation presented here is that of fuzzy state aggregation. This article presents the use of fuzzy state aggregation with the current policy hill climbing methods of Win or Lose Fast (WoLF) and policy-dynamics based WoLF (PD-WoLF), exceeding the learning rate …
Winning Back The Cup For Distributed Pomdps: Planning Over Continuous Belief Spaces, Pradeep Varakantham, Ranjit Nair, Milind Tambe, Makoto Yokoo
Winning Back The Cup For Distributed Pomdps: Planning Over Continuous Belief Spaces, Pradeep Varakantham, Ranjit Nair, Milind Tambe, Makoto Yokoo
Research Collection School Of Computing and Information Systems
Distributed Partially Observable Markov Decision Problems (Distributed POMDPs) are evolving as a popular approach for modeling multiagent systems, and many different algorithms have been proposed to obtain locally or globally optimal policies. Unfortunately, most of these algorithms have either been explicitly designed or experimentally evaluated assuming knowledge of a starting belief point, an assumption that often does not hold in complex, uncertain domains. Instead, in such domains, it is important for agents to explicitly plan over continuous belief spaces. This paper provides a novel algorithm to explicitly compute finite horizon policies over continuous belief spaces, without restricting the space of …
Evaluation Of Time-Varying Availability In Multi-Echelon Spare Parts Systems With Passivation, Hoong Chuin Lau, Huawei Song, Chuen Teck See, Siew Yen Cheng
Evaluation Of Time-Varying Availability In Multi-Echelon Spare Parts Systems With Passivation, Hoong Chuin Lau, Huawei Song, Chuen Teck See, Siew Yen Cheng
Research Collection School Of Computing and Information Systems
The popular models for repairable item inventory, both in the literature as well as practical applications, assume that the demands for items are independent of the number of working systems. However this assumption can introduce a serious underestimation of availability when the number of working systems is small, the failure rate is high or the repair time is long. In this paper, we study a multi-echelon repairable item inventory system under the phenomenon of passivation, i.e. serviceable items are passivated (“switched off”) upon system failure. This work is motivated by corrective maintenance of high-cost technical equipment in the miltary. We …
Examination Dialogue: An Argumentation Framework For Critically Questioning An Expert Opinion, Douglas Walton
Examination Dialogue: An Argumentation Framework For Critically Questioning An Expert Opinion, Douglas Walton
CRRAR Publications
Recent work in argumentation theory (Walton and Krabbe, 1995; Walton, 2005) and artificial intelligence (Bench-Capon, 1992, 2003; Cawsey, 1992; McBurney and Parsons, 2002; Bench-Capon and Prakken, 2005) uses types of dialogue as contexts of argument use. This paper provides an analysis of a special type called examination dialogue, in which one party questions another party, sometimes critically or even antagonistically, to try to find out what that party knows about something. This type of dialogue is most prominent in law and in both legal and non-legal arguments based on expert opinion. It is also central to dialogue systems for questioning …
Computer Models For Legal Prediction, Kevin D. Ashley, Stephanie Bruninghaus
Computer Models For Legal Prediction, Kevin D. Ashley, Stephanie Bruninghaus
Articles
Computerized algorithms for predicting the outcomes of legal problems can extract and present information from particular databases of cases to guide the legal analysis of new problems. They can have practical value despite the limitations that make reliance on predictions risky for other real-world purposes such as estimating settlement values. An algorithm's ability to generate reasonable legal arguments also is important. In this article, computerized prediction algorithms are compared not only in terms of accuracy, but also in terms of their ability to explain predictions and to integrate predictions and arguments. Our approach, the Issue-Based Prediction algorithm, is a program …
Visualization For Analyzing Trajectory-Based Metaheuristic Search Algorithms, Steven Halim, Roland H. C. Yap, Hoong Chuin Lau
Visualization For Analyzing Trajectory-Based Metaheuristic Search Algorithms, Steven Halim, Roland H. C. Yap, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
No abstract provided.
The History Of Computer Games, Jill Cirasella, Danny Kopec
The History Of Computer Games, Jill Cirasella, Danny Kopec
Publications and Research
This handout presents milestones in the history of computer backgammon, computer bridge, computer checkers, computer chess, computer Go, computer Othello, and computer poker.
Proximity In Context: An Empirically Grounded Computational Model Of Proximity For Processing Topological Spatial Expression., John D. Kelleher, Geert-Jan Kruijff, Fintan Costello
Proximity In Context: An Empirically Grounded Computational Model Of Proximity For Processing Topological Spatial Expression., John D. Kelleher, Geert-Jan Kruijff, Fintan Costello
Conference papers
The paper presents a new model for context-dependent interpretation of linguistic expressions about spatial proximity between objects in a natural scene. The paper discusses novel psycholinguistic experimental data that tests and verifies the model. The model has been implemented, and enables a conversational robot to identify objects in a scene through topological spatial relations (e.g. ''X near Y''). The model can help motivate the choice between topological and projective prepositions.
Incremental Generation Of Spatial Referring Expressions In Situated Dialogue, John D. Kelleher, Geert-Jan Kruijff
Incremental Generation Of Spatial Referring Expressions In Situated Dialogue, John D. Kelleher, Geert-Jan Kruijff
Conference papers
This paper presents an approach to incrementally generating locative expressions. It addresses the issue of combinatorial explosion inherent in the construction of relational context models by: (a) contextually defining the set of objects in the context that may function as a landmark, and (b) sequencing the order in which spatial relations are considered using a cognitively motivated hierarchy of relations, and visual and discourse salience.
A Computational Model Of The Referential Semantics Of Projective Prepositions, John D. Kelleher, Josef Van Genabith
A Computational Model Of The Referential Semantics Of Projective Prepositions, John D. Kelleher, Josef Van Genabith
Conference papers
In this paper we present a framework for interpreting locative expressions containing the prepositions in front of and behind. These prepositions have different semantics in the viewer-centred and intrinsic frames of reference (Vandeloise, 1991). We define a model of their semantics in each frame of reference. The basis of these models is a novel parameterized continuum function that creates a 3-D spatial template. In the intrinsic frame of reference the origin used by the continuum function is assumed to be known a priori and object occlusion does not impact on the applicability rating of a point in the spatial template. …
Multiagent Teamwork: Hybrid Approaches, Praveen Paruchuri, Emma Bowring, Ranjit Nair, Jonathan Pearce, Nathan Schurr, Milind Tambe, Pradeep Varakantham
Multiagent Teamwork: Hybrid Approaches, Praveen Paruchuri, Emma Bowring, Ranjit Nair, Jonathan Pearce, Nathan Schurr, Milind Tambe, Pradeep Varakantham
Research Collection School Of Computing and Information Systems
Today within the multiagent community, we see at least four competing methods to building multiagent systems: beliefdesireintention (BDI), distributed constraint optimization (DCOP), distributed POMDPs, and auctions or game-theoretic methods. While there is exciting progress within each approach, there is a lack of cross-cutting research. This article highlights the various hybrid techniques for multiagent teamwork developed by the teamcore group. In particular, for the past decade, the TEAMCORE research group has focused on building agent teams in complex, dynamic domains. While our early work was inspired by BDI, we will present an overview of recent research that uses DCOPs and distributed …
Hybrid Committee Classifier For A Computerized Colonic Polyp Detection System, Jiang Li, Jianhua Yao, Nicholas Petrick, Ronald M. Summers, Amy K. Hara, Joseph M. Reinhardt (Ed.), Josien P.W. Pluim (Ed.)
Hybrid Committee Classifier For A Computerized Colonic Polyp Detection System, Jiang Li, Jianhua Yao, Nicholas Petrick, Ronald M. Summers, Amy K. Hara, Joseph M. Reinhardt (Ed.), Josien P.W. Pluim (Ed.)
Electrical & Computer Engineering Faculty Publications
We present a hybrid committee classifier for computer-aided detection (CAD) of colonic polyps in CT colonography (CTC). The classifier involved an ensemble of support vector machines (SVM) and neural networks (NN) for classification, a progressive search algorithm for selecting a set of features used by the SVMs and a floating search algorithm for selecting features used by the NNs. A total of 102 quantitative features were calculated for each polyp candidate found by a prototype CAD system. 3 features were selected for each of 7 SVM classifiers which were then combined to form a committee of SVMs classifier. Similarly, features …