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RoboCup: The Robot World Cup Initiative
The Robot World Cup Initiative (R, oboCup) is attempt to foster AI and intelligent rohoties research by providing a standard problem where wide range of technologies especially concerning multi-agent…
RoboCup: A Challenge Problem for AI
- H. Kitano, M. Asada, Y. Kuniyoshi, I. Noda, Eiichi Osawa, H. Matsubara
- Computer ScienceAI Mag.
- 15 March 1997
Technical challenges involved in RoboCup, rules, and the simulation environment are described, including design principles of autonomous agents, multiagent collaboration, strategy acquisition, real-time reasoning, robotics, and sensor fusion.
Versatile visual servoing without knowledge of true Jacobian
The proposed visual servoing control scheme ensures the convergence of the image-features to desired trajectories, by using the estimated Jacobian matrix, which is proved by the Lyapunov stability theory.
Cognitive Developmental Robotics: A Survey
Cognitive developmental robotics aims to provide new understanding of how human's higher cognitive functions develop by means of a synthetic approach that developmentally constructs cognitive functions through interactions with the environment, including other agents.
Information processing in echo state networks at the edge of chaos
- J. Boedecker, Oliver Obst, J. Lizier, N. Mayer, M. Asada
- Computer ScienceTheory in Biosciences
- 1 September 2012
Evidence is presented that both information transfer and storage in the recurrent layer are maximized close to this phase transition, providing an explanation for why guiding the recurrent layers toward the edge of chaos is computationally useful.
RoboCup: A Challenge Problem for AI and Robotics
Technical challenges involved in RoboCup, rules, and simulation environment are described and a software platform for research on the software aspects of RoboCups is offered.
Cognitive developmental robotics as a new paradigm for the design of humanoid robots
Purposive Behavior Acquisition for a Real Robot by Vision-Based Reinforcement Learning
A method of vision-based reinforcement learning by which a robot learns to shoot a ball into a goal by using Learning from Easy Missions (or LEM), which reduces the learning time from exponential to almost linear order in the size of the state space.
The RoboCup Synthetic Agent Challenge 97
This paper presents three specific challenges for the next two years of RoboCup Challenge: learning of individual agents and teams; multi-agent team planning and plan-execution in service of teamwork; and opponent modeling.
A constructive model for the development of joint attention
The experimental results show that the proposed model makes the robot reproduce the developmental process of infants' joint attention, which could be one of the models to explain how infants develop the ability of joint attention.