A Two-Phase Mechanism for Agent's Action Selection in Soccer Simulation
نویسندگان
چکیده
Soccer simulation is an effort to motivate researchers and practitioners to do artificial and robotic intelligence research; and at the same time put into practice and test the results. Many researchers and practitioners throughout the world are continuously working to polish their ideas and improve their implemented systems. At the same time, new groups are forming and they bring bright new thoughts to the field. The research includes designing and executing robotic soccer simulation algorithms. In our research, a soccer simulation player is considered to be an intelligent agent that is capable of receiving information from the environment, analyze it and to choose the best action from a set of possible ones, for its next move. We concentrate on developing a two-phase method for the soccer player agent to choose its best next move. The method is then implemented into our software system called Nexus simulation team of Ferdowsi University. This system is based on TsinghuAeolus[1] team that was the champion of the world RoboCup soccer simulation contest in 2001 and 2002. Keywords—RoboCup, Soccer simulation, multi-agent environment, intelligent soccer agent, ball controller agent.
منابع مشابه
A simple method for decision making in robocup soccer simulation 3d environment
Un método simple para la toma de decisiones en ambientes 3D de simulación de fútbol RoboCup Abstract—In th is p ap er n ew hier ar ch ical hybr id fuzzycr isp methods for decision making and action selection of an agent in soccer simulation 3D environment are presented. First, the skills of an agent are introduced, imp lemented and classified in two layers, the basicskills and the highlevel ...
متن کاملEvolutionary Learning for Fuzzy Path Planning of Shooting Action for Robot Soccer
This paper proposes a new selection mechanism in evolutionary learning for fuzzy systems, which is applied to the learning of shooting action for robot soccer. In generic evolutionary algorithm, since the evaluation and the selection are performed on the level of chromosome, selected chromosome may include non-effective or bad genes, which increase the uncertainty of the solutions. To solve thi...
متن کاملLearning Decision Trees for Action Selection in Soccer Agents
In highly-dynamic domains such as robotic soccer it is important for agents to take action rapidly, often in the order of a fraction of a second. This requires, a possible longer-term planning component notwithstanding, some form of reactive action selection mechanism. In this paper we report on results employing decision-tree learning to provide a ball-possessing soccer agent in the S IMULATIO...
متن کاملSimultaneous Planning and Acting in Robotic Soccer
Performing coordinated real-time actions in an uncertain evolving environment requires interpreting noisy probabilistic information about a situation and acting based on these interpretations. This task becomes much more complex when the environment contains other agents, some of which antagonize each other. RoboCup (The World Cup Robot Soccer) is an attempt to promote AI and robotics research ...
متن کاملThe Effects of Short-Duration High-Intensity Soccer Fatigue Simulation on Dynamic Balance and Lower Limb Isokinetic Strength in Youth Soccer Players
Background. This study investigated the effects of short-duration high-intensity simulation of soccer fatigue on the dynamic balance and isokinetic strength of the lower limbs in youth soccer players. Methods. Thirty-nine youth soccer players completed a high-intensity fatigue simulation in 5-min. The participants performed tests on dynamic balance and isokinetic strength before the fatigue si...
متن کامل