Skip to search formSkip to main contentSkip to account menu
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…
View on ACM
RoboCup: A Challenge Problem for AI
TLDR
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.
View via Publisher
Versatile visual servoing without knowledge of true Jacobian
  • K. Hosoda, M. Asada
  • Engineering
    Proceedings of IEEE/RSJ International Conference…
  • 12 September 1994
TLDR
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.
View on IEEE
Cognitive Developmental Robotics: A Survey
TLDR
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.
View on IEEE
Information processing in echo state networks at the edge of chaos
TLDR
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.
View on Springer
RoboCup: A Challenge Problem for AI and Robotics
TLDR
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.
View via Publisher
Cognitive developmental robotics as a new paradigm for the design of humanoid robots
View via Publisher
Purposive Behavior Acquisition for a Real Robot by Vision-Based Reinforcement Learning
TLDR
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.
View on Springer
The RoboCup Synthetic Agent Challenge 97
TLDR
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.
View via Publisher
A constructive model for the development of joint attention
TLDR
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.
View on Taylor & Francis
...
...
By clicking accept or continuing to use the site, you agree to the terms outlined in our Privacy Policy, Terms of Service, and Dataset License