The Experts below are selected from a list of 22584 Experts worldwide ranked by ideXlab platform
Frank Schussele - One of the best experts on this subject based on the ideXlab platform.
-
ultimate taipan with symbolic interpretation and fluid Abstractions
Tools and Algorithms for Construction and Analysis of Systems, 2020Co-Authors: Daniel Dietsch, Matthias Heizmann, Alexander Nutz, Claus Schatzle, Frank SchusseleAbstract:Ultimate Taipan is a software model checker that combines trace Abstraction with abstract interpretation on path programs. In this year’s version, we replaced our abstract interpretation engine and now use a combination of Multiple Abstraction functions, fixpoint computation, algebraic program analysis, and SMT solving. Our new approach will allow us to integrate new techniques more easily.
-
TACAS (2) - Ultimate Taipan with Symbolic Interpretation and Fluid Abstractions
Tools and Algorithms for the Construction and Analysis of Systems, 2020Co-Authors: Daniel Dietsch, Matthias Heizmann, Alexander Nutz, Claus Schatzle, Frank SchusseleAbstract:Ultimate Taipan is a software model checker that combines trace Abstraction with abstract interpretation on path programs. In this year’s version, we replaced our abstract interpretation engine and now use a combination of Multiple Abstraction functions, fixpoint computation, algebraic program analysis, and SMT solving. Our new approach will allow us to integrate new techniques more easily.
Daniel Dietsch - One of the best experts on this subject based on the ideXlab platform.
-
ultimate taipan with symbolic interpretation and fluid Abstractions
Tools and Algorithms for Construction and Analysis of Systems, 2020Co-Authors: Daniel Dietsch, Matthias Heizmann, Alexander Nutz, Claus Schatzle, Frank SchusseleAbstract:Ultimate Taipan is a software model checker that combines trace Abstraction with abstract interpretation on path programs. In this year’s version, we replaced our abstract interpretation engine and now use a combination of Multiple Abstraction functions, fixpoint computation, algebraic program analysis, and SMT solving. Our new approach will allow us to integrate new techniques more easily.
-
TACAS (2) - Ultimate Taipan with Symbolic Interpretation and Fluid Abstractions
Tools and Algorithms for the Construction and Analysis of Systems, 2020Co-Authors: Daniel Dietsch, Matthias Heizmann, Alexander Nutz, Claus Schatzle, Frank SchusseleAbstract:Ultimate Taipan is a software model checker that combines trace Abstraction with abstract interpretation on path programs. In this year’s version, we replaced our abstract interpretation engine and now use a combination of Multiple Abstraction functions, fixpoint computation, algebraic program analysis, and SMT solving. Our new approach will allow us to integrate new techniques more easily.
Steven Susanto - One of the best experts on this subject based on the ideXlab platform.
-
experiments with Multiple Abstraction heuristics in symbolic verification
Symposium on Abstraction Reformulation and Approximation, 2005Co-Authors: Kairong Qian, Albert Nymeyer, Steven SusantoAbstract:In this work we investigate a symbolic heuristic search algorithm in a model checker. The symbolic search algorithm is built on a system that manipulates binary decision diagrams (BDDs). We study the performance of the search algorithm in terms of the number of BDD operations, size of the BDDs, number of nodes they contain and run-time. We study the heuristic distribution of the state space, we measure effort by computing the mean heuristic value, and we compare single and Multiple heuristics. In the case of Multiple heuristics, we consider admissible and non-admissible merge strategies. We experiment on problems from a variety of domains. We find that Multiple heuristics can perform significantly worse than single heuristics in symbolic search in at least one domain. In general, the effect of the heuristics on the symbolic search in the different domains varies markedly, and we conjecture that the different behaviour is caused by intrinsic differences in the characteristics of the state space.
-
SARA - Experiments with Multiple Abstraction heuristics in symbolic verification
Lecture Notes in Computer Science, 2005Co-Authors: Kairong Qian, Albert Nymeyer, Steven SusantoAbstract:In this work we investigate a symbolic heuristic search algorithm in a model checker. The symbolic search algorithm is built on a system that manipulates binary decision diagrams (BDDs). We study the performance of the search algorithm in terms of the number of BDD operations, size of the BDDs, number of nodes they contain and run-time. We study the heuristic distribution of the state space, we measure effort by computing the mean heuristic value, and we compare single and Multiple heuristics. In the case of Multiple heuristics, we consider admissible and non-admissible merge strategies. We experiment on problems from a variety of domains. We find that Multiple heuristics can perform significantly worse than single heuristics in symbolic search in at least one domain. In general, the effect of the heuristics on the symbolic search in the different domains varies markedly, and we conjecture that the different behaviour is caused by intrinsic differences in the characteristics of the state space.
Cipriano Galindo - One of the best experts on this subject based on the ideXlab platform.
-
Multiple Abstraction Hierarchies for Mobile Robot Operation in Large Environments
2007Co-Authors: Cipriano Galindo, Juan-antonio Fernndez-madrigal, Javier GonzalezAbstract:This book focuses on the efficient performance of mobile robots through the use of multi-hierarchical symbolic representations of the environment. A mobile robot intended to perform deliberative actions must possess some symbolic representation of its workspace, but such representations of real environments usually become so large that should be conveniently arranged in order to facilitate and, in some cases, make possible their use. Apart from the drawback of dealing with large amounts of information, other problems stand out when using symbolic representations. One is keeping the model properly optimized with respect to the robot tasks while maintaining it coherent with reality. Another one is the creation (or modification) of symbols from sensorial data. This book addresses all these issues considering symbolic multi-hierarchical structures. Such structures, based on the concept of Abstraction, allow a robot to speed up its operation in large environments. Practical solutions tested on real robots (for instance, a robotic wheelchair for elder people) are provided. The book is intended for PhD students and in general for robotics, computer science, and artificial intelligence researchers.
-
Abstraction and Multiple Abstraction in the symbolic modeling of the environment of mobile robots
Symposium on Abstraction Reformulation and Approximation, 2005Co-Authors: Juanantonio Fernandezmadrigal, Javier Gonzalez, Cipriano GalindoAbstract:Except for pure reactive robots, that do not work with any explicit representation of their world [1], an intelligent robot must possess some symbolic representation of its environment in order to reason, plan (prediction), and perform efficiently (due to the intractable amount of subsymbolic information acquired from the real world). We have been working on that area during the last decade, in particular exploring the advantages of using Abstraction and Multiple Abstraction for modeling the environment of a mobile robot. In this sense we have addressed the following main issues: – Automatic construction of the model. Assistive approaches (involving human operators) are possible [4] but limit the autonomy of the robot. – Automatic optimization (adaptation) of the model, for coping with the different situations that the robot may face during its operation without constructing an entirely new model each time from scratch. – Coherence between the symbols in the model and the real world. This must be addressed as a dynamic procedure since the real world changes continuously. –Efficiency in using the model. We believe that the best model for a given robot is the one that improves the most the robot's planning of operations. Up to now, we have been working on obtaining a comprehensive solution with Abstraction as a basis for coping with all these issues at once. In the next we describe in more detail our solutions to each one.
-
SARA - Abstraction and Multiple Abstraction in the symbolic modeling of the environment of mobile robots
Lecture Notes in Computer Science, 2005Co-Authors: Juan-antonio Fernández-madrigal, Javier Gonzalez, Cipriano GalindoAbstract:Except for pure reactive robots, that do not work with any explicit representation of their world [1], an intelligent robot must possess some symbolic representation of its environment in order to reason, plan (prediction), and perform efficiently (due to the intractable amount of subsymbolic information acquired from the real world). We have been working on that area during the last decade, in particular exploring the advantages of using Abstraction and Multiple Abstraction for modeling the environment of a mobile robot. In this sense we have addressed the following main issues: – Automatic construction of the model. Assistive approaches (involving human operators) are possible [4] but limit the autonomy of the robot. – Automatic optimization (adaptation) of the model, for coping with the different situations that the robot may face during its operation without constructing an entirely new model each time from scratch. – Coherence between the symbols in the model and the real world. This must be addressed as a dynamic procedure since the real world changes continuously. –Efficiency in using the model. We believe that the best model for a given robot is the one that improves the most the robot's planning of operations. Up to now, we have been working on obtaining a comprehensive solution with Abstraction as a basis for coping with all these issues at once. In the next we describe in more detail our solutions to each one.
-
interactive task planning through Multiple Abstraction application to assistant robotics
European Conference on Artificial Intelligence, 2004Co-Authors: Cipriano Galindo, Javier Gonzalez, Juanantonio FernandezmadrigalAbstract:Assistant robotics has become an emergent field within the robotic and artificial intelligence communities ([1],[2]). The main characteristic of assistant robots is that they are designed to serve non-expert people within their environment. They must plan and act efficiently to accomplish tasks specified in a human-like manner, i.e. "take this envelope to Peter’s office". Thus, an assistant robot must manage a symbolic model of its environment -its world modelthat involves human concepts. A human-inspired world representation can be used to endow assistant robots with that mentioned capability. It is stated in literature that humans widely use the mechanism of Abstraction ([3],[6],[8]). Abstraction allows humans to work with abstract concepts that group other, more particular concepts. For instance, when somebody refers to "my office" she/he is talking about an abstract concept, dropping unnecessary details like door, wall, table, chair, cabinet, etc. A robot managing a world model that includes human concepts allows users to specify tasks in a human-like manner. Furthermore, the user can also interact with the robot during the planning process since the robot reports an understandable plan to the human. The work presented in this paper is intended to jointly cover human interaction and task planning efficiency, by using a hierarchical model of the environment. For our purposes, a multihierarchical world model called Multi-AH-graph ([6],[7]) has been implemented with two hierarchies of Abstraction: the task planning hierarchy devoted to efficient task planning and the cognitive hierarchy engaged in human communication. The use of these two hierarchies requires a translation process to transform concepts from one hierarchy to the other, which is addressed in this paper. The paper is structured as follows. Section 2 briefly reviews the Multi-AH-graph model. Section 3 is devoted to describe the human interaction mechanism in robot task planning and its application to a real robotic application. Finally, some conclusions and future work are outlined.
-
ECAI - Interactive task planning through Multiple Abstraction: application to assistant robotics
2004Co-Authors: Cipriano Galindo, Javier Gonzalez, Juan-antonio Fernández-madrigalAbstract:Assistant robotics has become an emergent field within the robotic and artificial intelligence communities ([1],[2]). The main characteristic of assistant robots is that they are designed to serve non-expert people within their environment. They must plan and act efficiently to accomplish tasks specified in a human-like manner, i.e. "take this envelope to Peter’s office". Thus, an assistant robot must manage a symbolic model of its environment -its world modelthat involves human concepts. A human-inspired world representation can be used to endow assistant robots with that mentioned capability. It is stated in literature that humans widely use the mechanism of Abstraction ([3],[6],[8]). Abstraction allows humans to work with abstract concepts that group other, more particular concepts. For instance, when somebody refers to "my office" she/he is talking about an abstract concept, dropping unnecessary details like door, wall, table, chair, cabinet, etc. A robot managing a world model that includes human concepts allows users to specify tasks in a human-like manner. Furthermore, the user can also interact with the robot during the planning process since the robot reports an understandable plan to the human. The work presented in this paper is intended to jointly cover human interaction and task planning efficiency, by using a hierarchical model of the environment. For our purposes, a multihierarchical world model called Multi-AH-graph ([6],[7]) has been implemented with two hierarchies of Abstraction: the task planning hierarchy devoted to efficient task planning and the cognitive hierarchy engaged in human communication. The use of these two hierarchies requires a translation process to transform concepts from one hierarchy to the other, which is addressed in this paper. The paper is structured as follows. Section 2 briefly reviews the Multi-AH-graph model. Section 3 is devoted to describe the human interaction mechanism in robot task planning and its application to a real robotic application. Finally, some conclusions and future work are outlined.
Roger D. Chamberlain - One of the best experts on this subject based on the ideXlab platform.
-
MASCOTS - Analysis of a Simple Approach to Modeling Performance for Streaming Data Applications
2013 IEEE 21st International Symposium on Modelling Analysis and Simulation of Computer and Telecommunication Systems, 2013Co-Authors: Jonathan C. Beard, Roger D. ChamberlainAbstract:Current state of the art systems contain various types of multicore processors, General Purpose Graphics Processing Units (GPGPUs) and occasionally Digital Signal Processors (DSPs) or Field-Programmable Gate Arrays (FPGAs). With heterogeneity comes Multiple Abstraction layers that hide underlying complexity. While necessary to ease programmability of these systems, this hidden complexity makes quantitative performance modeling a difficult task. This paper outlines a computationally simple approach to modeling the overall throughput and buffering needs of a streaming application deployed on heterogeneous hardware.
-
ISPASS - Use of simple analytic performance models for streaming data applications deployed on diverse architectures
2013 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS), 2013Co-Authors: Jonathan C. Beard, Roger D. ChamberlainAbstract:Modern hardware is often heterogeneous. With heterogeneity comes Multiple Abstraction layers that hide underlying complex systems. This complexity makes quantitative performance modeling a difficult task. Designers of high-performance streaming applications for heterogeneous systems must contend with unpredictable and often non-generalizable models to predict performance of a particular application and hardware mapping. This paper outlines a computationally simple approach that can be used to model the overall throughput and buffering needs of a streaming application on heterogeneous hardware. The model presented is based upon a hybrid maximum flow and decomposed discrete queueing model. The utility of the model is assessed using a set of real and synthetic benchmarks with model predictions compared to measured application performance.