Crucial factors affecting cooperative multirobot learning

The effectiveness of multirobot learning in achieving optimal, cooperative solutions is potentially affected by various factors having to do with the nature and configuration of the robots and the nature and configuration of the robots and the nature of the learning entities. Varying one factor wrongly may lead to undesirable results. There is no reported work on how systematically to set up these factors. In this paper, we methodically test the effect of varying four common factors (reward scope, global information delay, diversity of robots, and number of robots) in a decentralized multirobot system, first in simulation and then on real robots. The results show that two of these factors, reward scope and global information delay, if set up incorrectly, can prevent optimal, cooperative solutions.

[1]  Maja J. Mataric,et al.  Reinforcement Learning in the Multi-Robot Domain , 1997, Auton. Robots.

[2]  Michael R. M. Jenkin,et al.  A taxonomy for multi-agent robotics , 1996, Auton. Robots.

[3]  Ronald C. Arkin,et al.  Cooperative multiagent robotic systems , 1998 .

[4]  James L. Kenkel,et al.  Introductory Statistics for Management and Economics , 1984 .

[5]  Pradeep K. Khosla,et al.  Crucial Factors Affecting Decentralized Multirobot Learning in an Object Manipulation Task , 2003 .

[6]  Holly A. Yanco,et al.  An adaptive communication protocol for cooperating mobile robots , 1993 .

[7]  Peter Norvig,et al.  Artificial Intelligence: A Modern Approach , 1995 .

[8]  Maja J. Mataric,et al.  Issues and approaches in the design of collective autonomous agents , 1995, Robotics Auton. Syst..

[9]  Phillip J. McKerrow,et al.  Introduction to robotics , 1991 .

[10]  Maja J. Mataric,et al.  Interaction and intelligent behavior , 1994 .

[11]  R. Arkin,et al.  Behavioral diversity in learning robot teams , 1998 .

[12]  Maja J. Mataric,et al.  Reward Functions for Accelerated Learning , 1994, ICML.

[13]  Tucker Balch.  Taxonomies of Multirobot Task and Reward , 2002 .

[14]  Lynne E. Parker,et al.  Heterogeneous multi-robot cooperation , 1994 .

[15]  Andrew W. Moore,et al.  Reinforcement Learning: A Survey , 1996, J. Artif. Intell. Res..

[16]  Maja J. Mataric,et al.  Using communication to reduce locality in distributed multiagent learning , 1997, J. Exp. Theor. Artif. Intell..

[17]  Erann Gat,et al.  Integrating Planning and Reacting in a Heterogeneous Asynchronous Architecture for Controlling Real-World Mobile Robots , 1992, AAAI.

[18]  Lynne E. Parker,et al.  ALLIANCE: an architecture for fault tolerant multirobot cooperation , 1998, IEEE Trans. Robotics Autom..

[19]  M. Buss,et al.  Self Organizing Robots Based on Cell Structures - CKBOT , 2002, IEEE International Workshop on Intelligent Robots.

[20]  Lynne E. Parker,et al.  L-ALLIANCE: Task-oriented multi-robot learning in behavior-based systems , 1996, Adv. Robotics.

[21]  Tucker R. Balch,et al.  Communication in reactive multiagent robotic systems , 1995, Auton. Robots.

[22]  Pradeep K. Khosla,et al.  The necessity of average rewards in cooperative multirobot learning , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).

[23]  Ben J. A. Kröse,et al.  Learning from delayed rewards , 1995, Robotics Auton. Syst..

[24]  Andrew B. Kahng,et al.  Cooperative Mobile Robotics: Antecedents and Directions , 1997, Auton. Robots.

[25]  Rodney A. Brooks,et al.  A Robust Layered Control Syste For A Mobile Robot , 2022 .

[26]  Chris Watkins,et al.  Learning from delayed rewards , 1989 .

[27]  Richard S. Sutton,et al.  Reinforcement Learning: An Introduction , 1998, IEEE Trans. Neural Networks.

[28]  Ronald C. Arkin,et al.  An Behavior-based Robotics , 1998 .

[29]  Tucker Balch,et al.  Behavioral diversity as multiagent cooperation , 1999, Optics East.

[30]  Tucker Balch,et al.  Reward and Diversity in Multirobot Foraging , 1999, IJCAI 1999.

[31]  Pradeep K. Khosla,et al.  Dynamic Task Selection: A Simple Structure for Multirobot system , 2000, DARS.

[32]  Andrew B. Kahng,et al.  Cooperative Mobile Robotics: Antecedents and Directions , 1995, Proceedings 1995 IEEE/RSJ International Conference on Intelligent Robots and Systems. Human Robot Interaction and Cooperative Robots.