A Neuroevolutionary Approach to Adaptive Multi-agent Teams

A multi-agent architecture called the Adaptive Team of Agents (ATA) is introduced, wherein homogeneous agents adopt specific roles in a team dynamically in order to address all the sub-tasks necessary to meet the team’s goals. Artificial neural networks are then trained by neuroevolution to produce an example of such a team, trained to solve the problem posed by a simple strategy game. The evolutionary algorithm is found to induce the necessary in situ adaptivity of behavior into the agents, even when controlled by stateless feed-forward networks.

[1]  Risto Miikkulainen,et al.  Evolving Stochastic Controller Networks for Intelligent Game Agents , 2006, 2006 IEEE International Conference on Evolutionary Computation.

[2]  Simon M. Lucas,et al.  Cellz: a simple dynamic game for testing evolutionary algorithms , 2004, Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753).

[3]  Risto Miikkulainen,et al.  Active Guidance for a Finless Rocket Using Neuroevolution , 2003, GECCO.

[4]  X. Yao.  Evolving Artificial Neural Networks , 1999 .

[5]  Sandip Sen,et al.  Co-adaptation in a Team , 1997 .

[6]  Risto Miikkulainen,et al.  Evolving Obstacle Avoidance Behavior in a Robot Arm , 1996 .

[7]  Mitchell A. Potter,et al.  EVOLVING NEURAL NETWORKS WITH COLLABORATIVE SPECIES , 2006 .

[8]  Risto Miikkulainen,et al.  Discovering Complex Othello Strategies through Evolutionary Neural Networks , 1995, Connect. Sci..

[9]  Risto Miikkulainen,et al.  COOPERATIVE COEVOLUTION OF MULTI-AGENT SYSTEMS , 2001 .

[10]  David E. Moriarty,et al.  Symbiotic Evolution of Neural Networks in Sequential Decision Tasks , 1997 .

[11]  Daniele Loiacono,et al.  Computational intelligence in games , 2012, GECCO '12.

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

[13]  Risto Miikkulainen,et al.  Evolving visibly intelligent behavior for embedded game agents , 2006 .

[14]  Risto Miikkulainen,et al.  Evolving Neural Networks to Play Go , 2004, Applied Intelligence.

[15]  Dario Floreano,et al.  Evolution of Altruistic Robots , 2008, WCCI.

[16]  Risto Miikkulainen,et al.  Exploiting Sensor Symmetries in Example-based Training for Intelligent Agents , 2006, 2006 IEEE Symposium on Computational Intelligence and Games.

[17]  Risto Miikkulainen,et al.  Online Interactive Neuro-evolution , 2000, Neural Processing Letters.

[18]  Hava T. Siegelmann,et al.  Analog computation via neural networks , 1993, [1993] The 2nd Israel Symposium on Theory and Computing Systems.

[19]  John E. Laird,et al.  Human-Level AI's Killer Application: Interactive Computer Games , 2000, AI Mag..

[20]  Lakhmi C. Jain,et al.  Computational Intelligence in Games , 2005, IEEE Transactions on Neural Networks.

[21]  Risto Miikkulainen,et al.  Learning Sequential Decision Tasks , 1995 .

[22]  Risto Miikkulainen,et al.  Evolving adaptive neural networks with and without adaptive synapses , 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..

[23]  Risto Miikkulainen,et al.  Solving Non-Markovian Control Tasks with Neuro-Evolution , 1999, IJCAI.

[24]  Risto Miikkulainen,et al.  Neuroevolution for adaptive teams , 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..

[25]  Risto Miikkulainen,et al.  Robust non-linear control through neuroevolution , 2003 .

[26]  George Cybenko,et al.  Approximation by superpositions of a sigmoidal function , 1989, Math. Control. Signals Syst..

[27]  Risto Miikkulainen,et al.  2-D Pole Balancing with Recurrent Evolutionary Networks , 1998 .

[28]  J. D. Schaffer,et al.  Combinations of genetic algorithms and neural networks: a survey of the state of the art , 1992, [Proceedings] COGANN-92: International Workshop on Combinations of Genetic Algorithms and Neural Networks.

[29]  Risto Miikkulainen,et al.  Real-time neuroevolution in the NERO video game , 2005, IEEE Transactions on Evolutionary Computation.