Access the full text.
Sign up today, get DeepDyve free for 14 days.
Kristina Lerman, A. Galstyan (2003)
Macroscopic analysis of adaptive task allocation in robotsProceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453), 2
Kristina Lerman, A. Galstyan (2002)
Mathematical Model of Foraging in a Group of Robots: Effect of InterferenceAutonomous Robots, 13
Hans Chalupsky, Yolanda Gil, Craig Knoblock, Kristina Lerman, Jean Oh, D. Pynadath, Thomas Russ, Milind Tambe (2001)
Electric Elves: Applying Agent Technology to Support Human Organizations
A. Ijspeert, A. Martinoli, A. Billard, L. Gambardella (2001)
Collaboration Through the Exploitation of Local Interactions in Autonomous Collective Robotics: The Stick Pulling ExperimentAutonomous Robots, 11
A. Winfield, Jin Sa, M. Fernández-Gago, C. Dixon, M. Fisher (2005)
On Formal Specification of Emergent Behaviours in Swarm Robotic SystemsInternational Journal of Advanced Robotic Systems, 2
S. Kornienko, O. Kornienko, P. Levi (2004)
European conference on artificial intelligence (ECAI-04)
C. Intanagonwiwat, R. Govindan, D. Estrin (2000)
Directed diffusion: a scalable and robust communication paradigm for sensor networks
R. Arkin, T. Balch (1998)
Cooperative multiagent robotic systems
Kristina Lerman, A. Galstyan, A. Martinoli, A. Ijspeert (2002)
A Macroscopic Analytical Model of Collaboration in Distributed Robotic SystemsArtificial Life, 7
N. Wirth (1971)
Program development by stepwise refinementCommun. ACM, 26
Kristina Lerman, A. Martinoli, A. Galstyan (2004)
A Review of Probabilistic Macroscopic Models for Swarm Robotic Systems
D. Bertsekas, J. Tsitsiklis (1999)
Gradient Convergence in Gradient methods with ErrorsSIAM J. Optim., 10
C. Harper, A. Winfield (2006)
A methodology for provably stable behaviour-based intelligent controlRobotics Auton. Syst., 54
S. Kornienko, O. Kornienko, P. Levi (2004)
Generation of Desired Emergent Behavior in Swarm of Micro-Robots
A. Winfield, Jin Sa, Carmen Fernández-Gago, C. Dixon, M. Fisher (2005)
On the Formal Specification of Emergent Behaviours of Swarm Robotics SystemsInternational Journal of Advanced Robotic Systems, 2
D. Bertsekas (1997)
Gradient convergence in gradient methods
K. Lerman, A. Martinoli, A. Galstyan (2005)
Swarm robotics workshop: state-of-the-art survey
Karl Sims (1994)
Evolving 3D Morphology and Behavior by CompetitionArtificial Life, 1
D. Kotz, G. Cybenko, R. Gray, Guofei Jiang, Ronald Peterson, M. Hofmann, Daria Chacón, K. Whitebread, J. Hendler (2000)
Performance Analysis of Mobile Agents for Filtering Data Streams on Wireless NetworksMobile Networks and Applications, 7
V. Crespi, G. Cybenko (2003)
Decentralized algorithms for sensor registrationProceedings of the International Joint Conference on Neural Networks, 2003., 1
G. Mcfarland (1986)
The benefits of bottom-up designACM SIGSOFT Softw. Eng. Notes, 11
A. Martinoli, K. Easton, W. Agassounon (2004)
Modeling Swarm Robotic Systems: a Case Study in Collaborative Distributed ManipulationThe International Journal of Robotics Research, 23
G. Cybenko, D. Rus (2005)
Agent-Based Systems Engineering
A. Martinoli, A. Ijspeert, L. Gambardella (1999)
A Probabilistic Model for Understanding and Comparing Collective Aggregation Mechansims
O. Holland, C. Melhuish (1999)
Stigmergy, Self-Organization, and Sorting in Collective RoboticsArtificial Life, 5
M. Pizka, A. Bauer (2004)
A brief top-down and bottom-up philosophy on software evolutionProceedings. 7th International Workshop on Principles of Software Evolution, 2004.
A. Andrew (1999)
Artificial Intelligence and Mobile RobotsKybernetes
P. Brézillon, Paolo Bouquet (1999)
Lecture Notes in Artificial Intelligence
A. Martinoli, A. J. Ijspeert, L. M. Gambardella (1999)
Proceedings of the 5th European conference on advances in artificial life (ECAL-99)
C. Kube, Hong Zhang (1996)
The use of perceptual cues in multi-robot box-pushingProceedings of IEEE International Conference on Robotics and Automation, 3
Chris Jones, M. Matarić (2003)
From local to global behavior in intelligent self-assembly2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422), 1
Y. Bar-Shalom, T. Kirubarajan, X. Li (2001)
Estimation with Applications to Tracking and Navigation
T. Isakowitz, A. Kamis, M. Koufaris (1998)
Reconciling top-down and bottom-up design approaches in RMMData Base, 29
John-Michael McNew, E. Klavins (2007)
A Grammatical Approach to Cooperative Control
Kristina Lerman, Chris Jones, A. Galstyan, M. Matarić (2006)
Analysis of Dynamic Task Allocation in Multi-Robot SystemsThe International Journal of Robotics Research, 25
Traditionally, two alternative design approaches have been available to engineers: top-down and bottom-up. In the top-down approach, the design process starts with specifying the global system state and assuming that each component has global knowledge of the system, as in a centralized approach. The solution is then decentralized by replacing global knowledge with communication. In the bottom-up approach, on the other hand, the design starts with specifying requirements and capabilities of individual components, and the global behavior is said to emerge out of interactions among constituent components and between components and the environment. In this paper we present a comparative study of both approaches with particular emphasis on applications to multi-agent system engineering and robotics. We outline the generic characteristics of both approaches from the MAS perspective, and identify three elements that we believe should serve as criteria for how and when to apply either of the approaches. We demonstrate our analysis on a specific example of load balancing problem in robotics. We also show that under certain assumptions on the communication and the external environment, both bottom-up and top-down methodologies produce very similar solutions.
Autonomous Robots – Springer Journals
Published: Jan 5, 2008
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Copy and paste the desired citation format or use the link below to download a file formatted for EndNote
Access the full text.
Sign up today, get DeepDyve free for 14 days.
All DeepDyve websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.