Coaching a simulated soccer team by opponent model recognition Export

@inproceedings{citeulike:3424799, abstract = {In multiagent domains with adversarial and cooperative agents, team agents should be adaptive to the current environment and opponent. We introduce an online method to provide the agents with team plans that a \“coach\” agent generates in response to the specific opponents. The coach agent is equipped with a number of pre-defined opponent models. The coach is then able to quickly select between different models online by using a naive Bayes style algorithm, making the planning adaptive to the current adversary. The coach uses a Simple Temporal Network to represent team plans as coordinated movements among the multiple agents and it searches for an opponent-dependent plan for its teammates. This plan is then communicated to the agents, who execute the plan in a distributed fashion. The system is fully implemented in a simulated robotic soccer domain.}, address = {New York, NY, USA}, author = {Riley, Patrick and Veloso, Manuela}, booktitle = {AGENTS '01: Proceedings of the fifth international conference on Autonomous agents}, citeulike-article-id = {3424799}, citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=376034}, citeulike-linkout-1 = {http://dx.doi.org/10.1145/375735.376034}, doi = {10.1145/375735.376034}, isbn = {1-58113-326-X}, keywords = {opponent-modelling, robocup}, location = {Montreal, Quebec, Canada}, pages = {155--156}, posted-at = {2008-10-17 17:04:59}, priority = {2}, publisher = {ACM}, title = {Coaching a simulated soccer team by opponent model recognition}, url = {http://dx.doi.org/10.1145/375735.376034}, year = {2001} }

TY - CONF ID - citeulike:3424799 L3 - citeulike-article-id:3424799 N2 - In multiagent domains with adversarial and cooperative agents, team agents should be adaptive to the current environment and opponent. We introduce an online method to provide the agents with team plans that a “coach” agent generates in response to the specific opponents. The coach agent is equipped with a number of pre-defined opponent models. The coach is then able to quickly select between different models online by using a naive Bayes style algorithm, making the planning adaptive to the current adversary. The coach uses a Simple Temporal Network to represent team plans as coordinated movements among the multiple agents and it searches for an opponent-dependent plan for its teammates. This plan is then communicated to the agents, who execute the plan in a distributed fashion. The system is fully implemented in a simulated robotic soccer domain. CY - Montreal, Quebec, Canada SN - 1-58113-326-X AD - New York, NY, USA EP - 156 TI - Coaching a simulated soccer team by opponent model recognition PB - ACM T2 - AGENTS '01: Proceedings of the fifth international conference on Autonomous agents SP - 155 KW - opponent-modelling KW - robocup AU - Riley, Patrick AU - Veloso, Manuela PY - 2001/// UR - http://dx.doi.org/10.1145/375735.376034 ER -