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Record Nr. |
UNINA9910700901903321 |
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Autore |
Eberts Randall W |
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Titolo |
Design, implementation, and evaluation of the Work First profiling pilot project [[electronic resource] /] / prepared for the Employment and Training Administration, U.S. Department of Labor ; by Randall W. Eberts |
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Pubbl/distr/stampa |
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[Washington, D.C.] : , : U.S. Dept. of Labor, Employment and Training Administration, , [2002] |
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Descrizione fisica |
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1 online resource (87 pages) |
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Collana |
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[ETA occasional paper ; ; 2002-07] |
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Soggetti |
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Welfare recipients - Employment - United States |
Unemployed - Services for - United States |
Employment agencies - United States |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Title from title screen (viewed July 27, 2004). |
"March 8, 2002." |
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2. |
Record Nr. |
UNINA9910143892803321 |
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Titolo |
Advances in Plan-Based Control of Robotic Agents : International Seminar, Dagstuhl Castle, Germany, October 21-26, 2001, Revised Papers / / edited by Michael Beetz, Leonidas Guibas, Joachim Herztberg, Malik Ghallab, Martha E. Pollack |
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Pubbl/distr/stampa |
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Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2002 |
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ISBN |
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Edizione |
[1st ed. 2002.] |
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Descrizione fisica |
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1 online resource (VIII, 296 p.) |
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Collana |
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Lecture Notes in Artificial Intelligence, , 2945-9141 ; ; 2466 |
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Disciplina |
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Soggetti |
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Automatic control |
Robotics |
Automation |
Artificial intelligence |
Computer science |
Control, Robotics, Automation |
Artificial Intelligence |
Computer Science |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Bibliographic Level Mode of Issuance: Monograph |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Plan-Based Multi-robot Cooperation -- Plan-Based Control for Autonomous Soccer Robots Preliminary Report -- Reliable Multi-robot Coordination Using Minimal Communication and Neural Prediction -- Collaborative Exploration of Unknown Environments with Teams of Mobile Robots -- Mental Models for Robot Control -- Perceptual Anchoring: A Key Concept for Plan Execution in Embedded Systems -- Progressive Planning for Mobile Robots A Progress Report -- Reasoning about Robot Actions: A Model Checking Approach -- Lifelong Planning for Mobile Robots -- Learning How to Combine Sensory-Motor Modalities for a Robust Behavior -- Execution-Time Plan Management for a Cognitive Orthotic System -- Path Planning for Cooperating Robots Using a GA-Fuzzy Approach -- Performance of a Distributed Robotic System Using Shared Communication Channels -- Use of |
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Cognitive Robotics Logic in a Double Helix Architecture for Autonomous Systems -- The dd&p Robot Control Architecture -- Decision-Theoretic Control of Planetary Rovers. |
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Sommario/riassunto |
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In recent years, autonomous robots, including Xavier, Martha [1], Rhino [2,3], Minerva,and Remote Agent, have shown impressive performance in long-term demonstrations. In NASA’s Deep Space program, for example, an - tonomous spacecraft controller, called the Remote Agent [5], has autonomously performed a scienti?c experiment in space. At Carnegie Mellon University, Xavier [6], another autonomous mobile robot, navigated through an o?ce - vironment for more than a year, allowing people to issue navigation commands and monitor their execution via the Internet. In 1998, Minerva [7] acted for 13 days as a museum tourguide in the Smithsonian Museum, and led several thousand people through an exhibition. These autonomous robots have in common that they rely on plan-based c- trol in order to achieve better problem-solving competence. In the plan-based approach, robots generate control actions by maintaining and executing a plan that is e?ective and has a high expected utility with respect to the robots’ c- rent goals and beliefs. Plans are robot control programs that a robot can not only execute but also reason about and manipulate [4]. Thus, a plan-based c- troller is able to manage and adapt the robot’s intended course of action — the plan — while executing it and can thereby better achieve complex and changing tasks. |
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