By Boer B., Kok J.
This thesis describes the incremental improvement and major positive aspects of an artificial multi-agent approach referred to as UvA Trilearn 2001. UvA Trilearn 2001 is a robot football simulation workforce that contains 11 self sustaining software program brokers. It operates in a actual football simulation method known as football server which allows groups of self sustaining software program brokers to play a video game of football opposed to one another. The football server offers a completely dispensed and real-time multi-agent surroundings during which teammates need to cooperate to accomplish their universal aim of successful the sport. The simulation types many real-world complexities corresponding to noise in item stream, noisy sensors and actuators, constrained actual talents and constrained communique. This thesis addresses some of the elements that make up the UvA Trilearn 2001 robot football simulation group and offers an perception into the way those elements were (incrementally) built. Our major contributions comprise a multi-threaded three-layer agent structure, a versatile agent-environment synchronization scheme, exact tools for item localization and speed estimation utilizing particle filters, a layered talents hierarchy, a scoring coverage for simulated football brokers and an efficient staff process. finally, the thesis will be considered as a guide for the improvement of an entire robot football simulation group which additionally comprises an creation to robot football often in addition to a survey of earlier study in football simulation. As such it presents a high-quality framework that may function a foundation for destiny learn within the box of simulated robot football. in the course of the venture UvA Trilearn 2001 has participated in overseas robot football competitions: the group reached fifth position on the German Open 2001 and 4th position on the legit RoboCup-2001 global championship.
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Extra info for The Incremental Development of a Synthetic Multi-Agent System: The UvA Trilcarn 2001 Robotic Soccer Simulation Team
By combining the known global positions of these landmarks with their relative positions (which are included in a visual message) an agent can determine his own global position and the global positions of the ball and other players. A player can directly control the frequency, range and quality of the visual information which is sent to him. The frequency with which visual information arrives from the server is determined by the server parameter send step, which represents the basic time step between visual messages and currently stands at 150ms.
27) where kick power rate is a server parameter which is used to determine the size of the acceleration vector and θ t is the direction in which the ball is accelerated in cycle t. This direction equals the sum of the body direction of the kicking player and the Angle parameter of the kick command. Furthermore, noise is added in the form of a small vector (k˜1 , k˜2 ) with k˜i a random number taken from a uniform distribution over the range [−kmax , kmax ]. 28) with kick rand a server parameter4 .
Messages from the referee however can be heard by all the players. 2 together with their default values. 2: Server parameters which are important for the aural sensor model with their default values. e. a player can say a message and hear one from another player simultaneously. CHAPTER 3. 3 26 Body Sensor Model The body sensor reports physical information about the player, such as its stamina, speed and neck angle. This information is automatically sent to the player every sense body step (in the current server version 100) ms.