Learning in multi-robot systems

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 1042, Issue , 1996, Pages 153-163

  Matarić, Maja J ^a  

^a BRANDEIS UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

INTELLIGENT AGENTS; LEARNING SYSTEMS; MULTIPURPOSE ROBOTS; REINFORCEMENT LEARNING;

DOMAIN KNOWLEDGE; MULTI-ROBOT SYSTEMS; PERCEPTION AND ACTIONS; POOR PERFORMANCE; TRADITIONAL REINFORCEMENTS;

MULTI AGENT SYSTEMS;

EID: 84949949419     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-60923-7_25     Document Type: Conference Paper

References (23)

1. Agre, P. E.& Chapman, D. (1990), What Are Plans for?, in P. Maes, ed., 'Designing Autonomous Agents: Theory and Practice from Biology to Engineering and Back', MIT Press, pp. 17-34.
2. Altenburg, K. (1994), Adaptive Resource Allocation for a Multiple Mobile Robot System using Communication, Technical Report NDSU—CSOR—TR-9404, North Dakota State Univeristy.
3. Arkin, R. C., Balch, T.& Nitz, E. (1993), Communication of Behavioral State in Multi-agent Retrieval Tasks, in 'IEEE International Conference on Robotics and Automation', pp. 588-594.
4. Atkeson, C. G. (1990), Memory-Based Approaches to Approximating Continuous Functions, in 'Proceedings, Sixth Yale Workshop on Adaptive and Learning Systems'.
5. Beckers, R., Holland, 0. E. & Deneubourg, J. L. (1994), From Local Actions to Global Tasks: Stigmergy and Collective Robotics, in R. Brooks & P. Maes, eds, 'Artificial Life IV, Proceedings of the Fourth International Workshop on the Synthesis and Simulation of Living Systems', MIT Press.
6. Brooks, R. A. (1990), The Behavior Language; User's Guide, Technical Report AIM-1127, MIT Artificial Intelligence Lab.
7. Donald, B. R., Jennings, J. & Rus, D. (1993), Information Invariants for Cooperating Autonomous Mobile Robots, in 'Proc. International Symposium on Robotics Research', Hidden Valley, PA.
8. Fukuda, T., Nadagawa, S., Kawauchi, Y. & Buss, M. (1989), Structure Decision for Self Organizing Robots Based on Cell Structures - CEBOT, in 'IEEE International Conference on Robotics and Automation', Scottsdale, Arizona, pp. 695-700.
9. Jaakkola, T. & Jordan, M. I. (1993), 'On the Convergence of Stochastic Iterative Dynamic Programming Algorithms', Submitted to Neural Computation.
10. Kaelbling, L. P. (1990), Learning in Embedded Systems, PhD thesis, Stanford University.
11. Maes, P. & Brooks, R. A. (1990), Learning to Coordinate Behaviors, in 'Proceedings, AAAI-91', Boston, MA, pp. 796-802.
12. Mahadevan, S. & Connell, J. (1991), Automatic Programming of Behavior-based Robots using Reinforcement Learning, in 'Proceedings, AAAI-91', Pittsburgh, PA, pp. 8-14.
13. MatariC, M. J. (1992), Designing Emergent Behaviors: From Local Interactions to Collective Intelligence, in J.-A. Meyer, H. Roitblat & S. Wilson, eds, 'From Animals to Animats: International Conference on Simulation of Adaptive Behavior'.
14. MatariC, M. J. (1994), Interaction and Intelligent Behavior, Technical Report AI-TR-1495, MIT Artificial Intelligence Lab.
15. MatariC, M. J.. (1995), Evaluation of Learning Performance of Situated Embodied Agents, in 'Proceedings, Advances in Artificial Life, Third European Conference on Artificial Life (ECAL)', pp. 579-589.
16. North's, F. R. (1993), 'Toward a Robot Architecture Integrating Cooperation between Mobile Robots: Application to Indoor Environment', The International Journal of Robotics Research 12(1), 79-98.
17. Parker, L. E. (1994), Heterogeneous Multi—Robot Cooperation, PhD thesis, MIT. Simsarian, K. T. & MatariC, M. J. (1995), Learning to Cooperate Using Two Six—Legged Mobile Robots, in 'Proceedings, Third European Workshop of LearningRobots', Heraklion, Crete, Greece.
18. Singh, S. P. (1991), Transfer of Learning Across Compositions of Sequential Tasks, in 'Proceedings, Eighth International Conference on Machine Learning', Morgan Kaufmann, Evanston, Illinois, pp. 348-352.
19. Sutton, R. (1988), 'Learning to Predict by Method of Temporal Differences', Machine Learning 3(1), 9-44.
20. Tan, M. (1993), Multi-Agent Reinforcement Learning: Independent vs. Cooperative Agents, in 'Proceedings, Tenth International Conference on Machine Learning', Amherst, MA, pp. 330-337.
21. Watkins, C. J. C. H. (1989), Learning from Delayed Rewards, PhD thesis, King's College, Cambridge.
22. Whitehead, S. D. (1992), Reinforcement Learning for the Adaptive Control of Perception and Action, PhD thesis, University of Rochester.
23. Whitehead, S. D., Karlsson, J. & Tenenberg, J. (1993), Learning Multiple Goal Behavior via Task Decomposition and Dynamic Policy Merging, in J. H. Connell & S. Mahadevan, eds, 'Robot Learning', Kluwer Academic Publishers, pp. 45-78.