Exploiting learning techniques for the acquisition of user stereotypes and communities
UM '99 Proceedings of the seventh international conference on User modeling
Coaching a simulated soccer team by opponent model recognition
Proceedings of the fifth international conference on Autonomous agents
Layered Learning in Multiagent Systems: A Winning Approach to Robotic Soccer
Layered Learning in Multiagent Systems: A Winning Approach to Robotic Soccer
Machine Learning for User Modeling
User Modeling and User-Adapted Interaction
Machines that learn to play games
Machines that learn to play games
Learning Hierarchical Performance Knowledge by Observation
ICML '99 Proceedings of the Sixteenth International Conference on Machine Learning
From Interaction Data to Plan Libraries: A Clustering Approach
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Opponent Modeling in Multi-Agent Systems
IJCAI '95 Proceedings of the Workshop on Adaption and Learning in Multi-Agent Systems
Co-evolving Soccer Softbot Team Coordination with Genetic Programming
RoboCup-97: Robot Soccer World Cup I
Using ABC2 in the RoboCup Domain
RoboCup-97: Robot Soccer World Cup I
A Framework for Behavioural Cloning
Machine Intelligence 15, Intelligent Agents [St. Catherine's College, Oxford, July 1995]
Multiagent learning in the presence of agents with limitations
Multiagent learning in the presence of agents with limitations
Skill reconstruction as induction of LQ controllers with subgoals
IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
Machine learning of user profiles: representational issues
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Evolution of reactive rules in multi player computer games based on imitation
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part II
Controller for TORCS created by imitation
CIG'09 Proceedings of the 5th international conference on Computational Intelligence and Games
Formal specification of an immune based agent architecture
Engineering Applications of Artificial Intelligence
Situational programming: agent behavior visual programming for MABS novices
MABS'10 Proceedings of the 11th international conference on Multi-agent-based simulation
Adapting Searchy to extract data using evolved wrappers
Expert Systems with Applications: An International Journal
Local Models for data-driven learning of control policies for complex systems
Expert Systems with Applications: An International Journal
On teaching collaboration to a team of autonomous agents via imitation
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Hi-index | 12.05 |
The Robosoccer simulator is a challenging environment for artificial intelligence, where a human has to program a team of agents and introduce it into a soccer virtual environment. Most usually, Robosoccer agents are programmed by hand. In some cases, agents make use of Machine learning (ML) to adapt and predict the behavior of the opposite team, but the bulk of the agent has been preprogrammed. The main aim of this paper is to transform Robosoccer into an interactive game and let a human control a Robosoccer agent. Then ML techniques can be used to model his/her behavior from training instances generated during the play. This model will be used later to control a Robosoccer agent, thus imitating the human behavior. We have focused our research on low-level behavior, like looking for the ball, conducting the ball towards the goal, or scoring in the presence of opponent players. Results have shown that indeed, Robosoccer agents can be controlled by programs that model human play.