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robot soccer layered learning

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Layered Learning for a Soccer Legged Robot Helped with a 3D ...

Cherubini A., Giannone F., Iocchi L. (2008) Layered Learning for a Soccer Legged Robot Helped with a 3D Simulator. In: Visser U., Ribeiro F., Ohashi T., Dellaert F. (eds) RoboCup 2007: Robot Soccer World Cup XI. RoboCup 2007. Lecture Notes in Computer Science, vol 5001. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68847-1_39

Layered Learning in Genetic Programming for a Cooperative ...

This method is applied to evolve agents to play keep-away soccer, a subproblem of robotic soccer that requires cooperation among multiple agents in a dynnamic environment. The layered learning paradigm allows GP to evolve better solutions faster than standard GP.

A Layered Approach to Learning Client Behaviors in the ...

Our approach to using ML as a tool for building Soccer Server clients involves layering increasingly complex learned behaviors. We call this approach layered learning. Because of the complexity of the domain, it is futile to try to learn intelligent behaviors straight from the primitives provided by the server.

Copyright by Anand Subramoney 2012

current layered learning and co-evolution in the robot soccer domain is the pri-mary focus of study. This thesis does a comprehensive study of various variants of the ESP neuroevolution algorithm used in various learning methodologies in the robot soccer keepaway task, using the robocup soccer simulator.

Policy gradient learning for quadruped soccer robots ...

A. Cherubini, F. Giannone, L. Iocchi, Layered learning for a soccer legged robot helped with a 3D simulator, in: RoboCup 2007: Robot Soccer World Cup XI, 2008, pp. 385–392. Google Scholar [8]

Journal Logo - cs.utexas.edu

Cherubini et al. used layered learning for teaching AIBO robots soccer skills that included six behaviors [24]. Layered learning has also been applied to non-RoboCup domains such as Boolean logic [25], non-playable characters in video games [26], and concept synthesis in road traffic simulations [27].

AI-Lab - Learning Agents

A Study of Layered Learning Strategies Applied to Individual Behaviors in Robot Soccer: 2016 : David L. Leottau, Javier Ruiz-del-Solar, Patrick MacAlpine, and Peter Stone, In {R}obo{C}up-2015: Robot Soccer World Cup {XIX}, Luis Almeida and Jianmin Ji and Gerald Steinbauer and Sean Luke (Eds.), Berlin, Germany 2016. Springer Verlag.

Robot Soccer Players Learning Fancy Human Skills - IEEE Spectrum

Robot Soccer Players Learning Fancy Human Skills. Share. ... RoboCup 2011 just kicked off in Istanbul, and the robot soccer players are already demonstrating some slick footwork.

Evaluation-function modeling with multi-layered perceptron ...

In the RoboCup soccer simulation 2D league, players make a decision at each cycle in real time. The performance of a team highly depends on the agents’ decision-making process, which is composed of a action planning method and an evaluation function of the soccer field. In this work, a cooperative action planning based on the tree search is employed. Each action is evaluated by an evaluation ...

Layered Learning | SpringerLink

Given a hierarchical task decomposition into subtasks, layered learning seamlessly integrates separate learning at each subtask layer. The learning of each subtask directly facilitates the learning of the next higher subtask layer by determining at least one of three of its components: (i) the set of training examples; (ii) the input representation; and/or (iii) the output representation. We introduce layered learning in its domain-independent general form. We then present a full ...