this report describes the culmination of the 13th installment of the "Adaptive Computing (and Agents) for Enhanced Collaboration" (ACEC) track. ACEC focuses on collaborative computing that occurs dynamically...
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Inverse optimal control (IOC) is a powerful approach for learning robotic controllers from demonstration that estimates a cost function which rationalizes demonstrated control trajectories. Unfortunately, its applicab...
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ISBN:
(纸本)9781577357384
Inverse optimal control (IOC) is a powerful approach for learning robotic controllers from demonstration that estimates a cost function which rationalizes demonstrated control trajectories. Unfortunately, its applicability is difficult in settings where optimal control can only be solved approximately. While local IOC approaches have been shown to successfully learn cost functions in such settings, they rely on the availability of good reference trajectories, which might not be available at test time. We address the problem of using IOC in these computationally challenging control tasks by using a graph-based discretization of the trajectory space. Our approach projects continuous demonstrations onto this discrete graph, where a cost function can be tractably learned via IOC. Discrete control trajectories from the graph are then projected back to the original space and locally optimized using the learned cost function. We demonstrate the effectiveness of the approach with experiments conducted on two 7-degree of freedom robotic arms.
Travel lights are more and more popular. Many residents and travelers enjoy traveling using bikes in Taiwan. Hence, this study designs a Cloud-based Bike-fleet POI Touring Service Platform, which is called C-BOOST, to...
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ISBN:
(纸本)9781510812277
Travel lights are more and more popular. Many residents and travelers enjoy traveling using bikes in Taiwan. Hence, this study designs a Cloud-based Bike-fleet POI Touring Service Platform, which is called C-BOOST, to help people make travel plans. C-BOOST is composed of Bikers and a Cloud-based Digital Convergence Server (CDCS). Bikers can use a smart-phone to get potential Point of Interests (POIs), to get Location-based Services (LBSs), to update traveling itineraries and to manage bike-fleets. Cloud-based Digital Convergence Server is based on Mass Behaviors Model, which provides RSS, Google App Engine (GAE) and Quality control Adaptor services. Quality control Adaptor is composed of Ant Colony Optimization (ACO) algorithm, Bayesian Network and Ontology by users' preferences and GPS values, providing potential POIs for bikers. C-BOOST can provide more suitable POIs for bikers.
Recently, several Web-scale knowledge harvesting systems have been built, each of which is competent at extracting information from certain types of data (e.g., unstructured text, structured tables on the web, etc.). ...
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ISBN:
(纸本)9781577357384
Recently, several Web-scale knowledge harvesting systems have been built, each of which is competent at extracting information from certain types of data (e.g., unstructured text, structured tables on the web, etc.). In order to determine the response to a new query posed to such systems (e.g., is sugar a healthy food?), it is useful to integrate opinions from multiple systems. If a response is desired within a specific time budget (e.g., in less than 2 seconds), then maybe only a subset of these resources can be queried. In this paper, we address the problem of knowledge integration for on-demand time-budgeted query answering. We propose a new method, AskWorld, which learns a policy that chooses which queries to send to which resources, by accommodating varying budget constraints that are available only at query (test) time. through extensive experiments on real world datasets, we demonstrate AskWorld's capability in selecting most informative resources to query within test-time constraints, resulting in improved performance compared to competitive baselines.
Service-Oriented Revision control (SORC) is a novel distributed Software Configuration Management (SCM) model specifically designed for *** supporting collaborative programming of Web applications, where each develope...
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We study pushdown systems where control states, stack alphabet, and transition relation, instead of being finite, are first-order definable in a fixed countably-infinite structure. We show that the reachability analys...
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the proceedings contain 19 papers. the special focus in this conference is on Program Analysis and Transformation, Constraint Handling Rules, Termination Analysis, Security and Program Testing and Verification. the to...
ISBN:
(纸本)9783319178219
the proceedings contain 19 papers. the special focus in this conference is on Program Analysis and Transformation, Constraint Handling Rules, Termination Analysis, Security and Program Testing and Verification. the topics include: Analyzing array manipulating programs by program transformation;analysing and compiling coroutines with abstract conjunctive partial deduction;confluence modulo equivalence in constraint handling rules;exhaustive execution of CHR through source-to-source transformation;a formal semantics for the cognitive architecture ACT-R;chranimation: an animation tool for constraint handling rules;extending the 2D dependency pair framework for conditional term rewriting systems;partial evaluation for java malware detection;access control and obligations in the category-based metamodel;concolic execution and test case generation in prolog;liveness properties in cafeOBJ - a case study for meta-level specifications;a hybrid method for the verification and synthesis of parameterized self-stabilizing protocols;drill and join:;functional kleene closures;on completeness of logic programs;polynomial approximation to well-founded semantics for logic programs with generalized atoms;declarative compilation for constraint logic programming and pre-indexed terms for prolog.
this report describes the culmination of the 13th installment of the “Adaptive Computing (and Agents) for Enhanced Collaboration” (ACEC) track. ACEC focuses on collaborative computing that occurs dynamically among W...
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this report describes the culmination of the 13th installment of the “Adaptive Computing (and Agents) for Enhanced Collaboration” (ACEC) track. ACEC focuses on collaborative computing that occurs dynamically among Web-accessible software systems and devices. the articulation of these network artifacts must be controlled by adaptive, intelligent control mechanisms, sometimes realized as agents. ACEC has for over 13 years brought together researchers from multiple disciplines to address the challenges associated with effective, just-in-time collaboration. the track this year showcases papers that explore emerging models and design patterns for adaptive architectures for a varied set of domains such as robotic and crowdsourcing.
Although supporting Quality of Service (QoS) on the traditional Internet has been extremely challenging, QoS supports are still highly desirable for many real-time applications. While existing QoS schemes often show p...
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Although supporting Quality of Service (QoS) on the traditional Internet has been extremely challenging, QoS supports are still highly desirable for many real-time applications. While existing QoS schemes often show poor scalability, low efficiency, and limited QoS supports, the fast development of Software Define Networks (SDNs) provides new opportunities to address QoS support with its centralized network control. In this paper, we propose a synchronized architecture to exploit the unique features of SDNs without conducting static reservations. Assume all routers are synchronized in time, we can precisely determine the upstream delay of a packet at a router. Meanwhile, because we also know the fairly accurate resource availability on its downstream routers (from the SDN controller), we can determine the packet's service priority on its current router based on its end-to-end (e2e) delay requirement and the expected delay that the packet may experience in its downstream. In particular, we propose a synchronized multi-hop scheduling (SMS) scheme to exploit both upstream information and downstream resource availability to speed up or slow down a packet. this is completely different from all existing per-hop or multi-hop schemes that mostly utilize upstream information. Furthermore, we propose to selectively drop a packet that is unlikely to meet its deadline. Our simulation results show that the proposed scheme outperforms existing schemes in packet missing rates.
In this paper an artificial neural network (ANN) is developed for modeling and controlling unknown chaotic systems to unstable periodic orbits (UPOs). In the modeling phase, the ANN is trained on the unknown chaotic s...
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