Simulated Soccer Research Articles

Preliminary Observations on Physiological Responses of Three Turfgrass Species to Traffic Stress

Traffic stress causes turfgrass injury and soil compaction but the underlying physiological mechanisms are not well documented. The objectives of this study were to investigate the physiological responses of kentucky bluegrass (Poa pratensis), tall fescue (Festuca arundinacea), and japanese zoysiagrass (Zoysia japonica) to three levels of traffic stress during the growing season under simulated soccer traffic conditions. Relative leaf water content (LWC), shoot density, leaf chlorophyll concentration (LCC), membrane permeability, and leaf antioxidant peroxidase (POD) activity were measured once per month. The traffic stress treatments caused a reduction in LWC, shoot density, LCC, and POD activity, and an increase in cell membrane permeability in all three species. Japanese zoysiagrass had less electrolyte leakage, and higher POD activity and shoot density than both kentucky bluegrass and tall fescue. The results suggest that turfgrass tolerance to traffic stress may be related to leaf antioxidant activity. Turfgrass species or cultivars with higher leaf antioxidant activity may be more tolerant to traffic stress than those with lower antioxidant activity.

The Effects of Low and High Glycemic Index Foods on Metabolism and Performance During a Simulated Soccer Match

The Effects of Low and High Glycemic Index Foods on Metabolism and Performance During a Simulated Soccer Match

A Novel Action Selection Architecture in Soccer Simulation Environment Using Neuro-Fuzzy and Bidirectional Neural Networks

Multi-Agent systems have generated lots of excitement in recent years because of its promise as a new paradigm for conceptualizing, designing, and implementing software systems. One of the most important aspects of agent design in AI is the way agent acts or responds to the environment that the agent is acting upon. An effective action selection and behavioral method gives a powerful advantage in overall agent performance. We define a new method of action selection based on probability/priority models, we thereby introduce two efficient ways to determine probabilities using neuro-fuzzy systems and bidirectional neural networks and a new priority based system which maps the human knowledge to the action selection method. Furthermore, a behavior model is introduced to make the model more flexible.

Modelling and simulation of a group of mobile robots

In this paper the mathematical background of the developed robot soccer simulator is presented. It involves robot and ball dynamic behaviour and focuses mainly on their collisions study. Vital parts of the simulator are explained and modelled in more detail, beginning with the simple model of ball and robot motion and continuing with a more complex approximate collisions models, where the real robot shape is taken into consideration. Some new ideas of collision formulation, realization and real robot shape inclusion are used. The implementation of the simulator is described and advantages for the usage of the realistic simulator are stated.

2A1-L10 分散アプリケーション開発用ツールキットによるマルチエージェントシステムに関する研究(進化・学習とロボティクス)

The toolkit is developed to support system developers for developing distributed application systems composed of a set of software components in a network computation environment which consists of Personal Computer, Engineering Work Station, Computerized Controller, and so on connected by LAN or Wave LAN. The software-tool provides Inter-components Communication, Remote Procedure Call, Components Migration/Replication, and Dynamic Components Binding/Unbinding to application systems as well as network transparency. The configuration and reconfiguration capabilities of application systems can be improved by applying these functions provided by this toolkit, and also high efficiency is expected to develop of distributed application systems. This paper describes a tool kit and a general idea of a process to develop a distributed application system by using the thing which developed and soccer simulation and a traffic simulation.

FUZZY STATE AGGREGATION AND POLICY HILL CLIMBING FOR STOCHASTIC ENVIRONMENTS

Reinforcement learning is one of the more attractive machine learning technologies, due to its unsupervised learning structure and ability to continually learn even as the operating environment changes. Additionally, by applying reinforcement learning to multiple cooperative software agents (a multi-agent system) not only allows each individual agent to learn from its own experience, but also opens up the opportunity for the individual agents to learn from the other agents in the system, thus accelerating the rate of learning. This research presents the novel use of fuzzy state aggregation, as the means of function approximation, combined with the fastest policy hill climbing methods of Win or Lose Fast (WoLF) and policy-dynamics based WoLF (PD-WoLF). The combination of fast policy hill climbing and fuzzy state aggregation function approximation is tested in two stochastic environments: Tileworld and the simulated robot soccer domain, RoboCup. The Tileworld results demonstrate that a single agent using the combination of FSA and PHC learns quicker and performs better than combined fuzzy state aggregation and Q-learning reinforcement learning alone. Results from the multi-agent RoboCup domain again illustrate that the policy hill climbing algorithms perform better than Q-learning alone in a multi-agent environment. The learning is further enhanced by allowing the agents to share their experience through a weighted strategy sharing.

Progressive Decrease in Dynamic Postural Control During Simulated Soccer Match-Play

This study investigated the cumulative effect of soccer-specific fatigue on dynamic posturography. Professional soccer players (N = 8) completed a treadmill protocol, which comprised two 45-minute exercise periods separated by a 15-minute interval (simulation of half-time). A 15-minute activity profile was developed, which was repeated six times in total. The 15-minute activity profile comprised 195 discrete bouts of exercise, producing a change in speed every ~6 seconds. Within this activity profile, seven movement speeds were included. Center of gravity displacement tended to increase as a function of exercise duration during each simulated half, with second half performance typically impaired more than in the first half. This trend was evident for total, medio-lateral and anterio-posterior displacement. During the plantar rotation trial, the passive half-time interval was observed to significantly increase medio-lateral displacement of the ankle. The intermittent activity profile of soccer match-play induced a significant deterioration in dynamic postural response as exercise progressed. Reduction in joint stability predisposed the ankle joint complex to sprain injury during the latter stages of match-play. Furthermore, a passive half-time strategy predisposed the ankle joint to injury during the early stages of the second half. [For baseball. Fatigue that occurs from pitching when not conditioned specifically for pitching, increases the likelihood of injury at the end of the pitching bout. When no activity occurs between-innings, the sudden resumption of violent pitching exercise also increases the likelihood of joint injuries (e.g., hamstrings, ankles, elbows). Thus, increasing specific pitching fitness and maintaining an active recovery during innings should reduce the likelihood of injury during a game.]

Coach planning with opponent models for distributed execution

In multi-agent domains, the generation and coordinated execution of plans in the presence of adversaries is a significant challenge. In our research, a special agent works with a team of distributed agents. The coach has a global view of the world, but has no actions other than occasionally communicating with the team over a limited bandwidth channel. Our coach is given a set of predefined opponent models which predict future states of the world caused by the opponents' actions. The coach observes the world state changes resulting from the execution of its team and opponents and selects the best matched opponent model based on its observations. The coach uses the recognized opponent model to predict the behavior of the opponent. Upon opportunities to communicate, the coach generates a plan for the team, using the predictions of the opponent model. The centralized coach generates a plan for distributed execution. We introduce (i) the probabilistic representation and recognition algorithm for the opponent models; (ii) a multi-agent plan representation, Multi-Agent Simple Temporal Networks; and (iii) a plan execution algorithm that allows the robust distributed execution in the presence of noisy perception and actions. The complete approach is implemented in a complex simulated robot soccer environment. We present the contributions as developed in this domain, carefully highlighting their generality along with a series of experiments validating the effectiveness of our coach approach.

FUZZY REINFORCEMENT LEARNING FOR EMBEDDED SOCCER AGENTS IN A MULTI-AGENT CONTEXT

The work presented in this paper aims at combining fuzzy function approximation and reinforcement learning in order to create robotic soccer agents that are able to coordinate their behaviours locally and socially while learning from experience. This simultaneous coordination and learning ability can play a crucial role in improving the behaviour usage of robotic soccer agents. To achieve this goal, a fuzzy reinforcement learning technique for a single agent is first examined and then this technique is applied to multiple agents. The conducted experiments through a soccer simulation system show that the performance of robot scoring speed is improved using the proposed approach.

Team Formation Construction Using a GUI Tool in the RoboCup Soccer Simulation

Team Formation Construction Using a GUI Tool in the RoboCup Soccer Simulation

FC PORTUGAL: DEVELOPMENT AND EVALUATION OF A NEW ROBOCUP RESCUE TEAM

FC Portugal Rescue team is the result of a cooperation project between the Universities of Aveiro and Porto in Portugal. Following previous collaborations of these two Portuguese Universities in RoboCup simulation league and associated competitions, this project intends to fully adapt the coordination methodologies developed by FC Portugal simulated soccer team to the search and rescue scenario. After FC Portugal's first successful participation in RoboCup rescue simulation league (Osaka, 2005), the team aimed at introducing new high-level strategic analysis tools in the Rescue league and developed FCPx tool. This tool enables an easy comparison of different teams' strategies, and the use of learning methodologies for high-level strategic decisions in rescue. The tool also enabled us to evaluate our coordination methodologies, analysing the results achieved in several rescue parameters, and conclude that they are very promising for the search and rescue domain. FC Portugal Rescue team results are very promising achieving first place in RoboCup European Championship 2006 (Dutch Open) held in Eindhoven.

Reinforcement Learning for RoboCup Soccer Keepaway

RoboCup simulated soccer presents many challenges to reinforcement learning methods, including a large state space, hidden and uncertain state, multiple independent agents learning simultaneously, and long and variable delays in the effects of actions. We describe our application of episodic SMDP Sarsa(λ) with linear tile-coding function approximation and variable λ to learning higher-level decisions in a keepaway subtask of RoboCup soccer. In keepaway, one team, “the keepers,” tries to keep control of the ball for as long as possible despite the efforts of “the takers.” The keepers learn individually when to hold the ball and when to pass to a teammate. Our agents learned policies that significantly outperform a range of benchmark policies. We demonstrate the generality of our approach by applying it to a number of task variations including different field sizes and different numbers of players on each team.

Effects of Phosphatidylserine on Oxidative Stress following Intermittent Running

The aim of the study was to investigate the effects of 750 mg of soybean-derived phosphatidylserine or a glucose polymer placebo, administered daily for 10 d, on markers of oxidative stress, perceived soreness, and muscle damage initiated by intermittent exercise (designed to simulated soccer match play) immediately followed by an exhaustive run. Following familiarization, 16 male soccer players completed an exhaustive intermittent exercise protocol on two further occasions (T1 and T2) separated by approximately 14 d. Ten days before T2, the subjects were assigned, in a double-blind manner, to receive either phosphatidylserine (PS) or a placebo (P). Exercise time to exhaustion, sprint performance, ratings of perceived exertion, and HR were recorded throughout both main exercise trials. Venous blood samples were obtained at rest (preexercise), 15 min following exercise (postexercise), 24 h after exercise (post-24 h), and 48 h after exercise (post-48 h). Preexercise and postexercise concentrations of plasma gamma-tocopherol were increased following supplementation in PS, although supplementation had no effect on plasma concentrations of other nonenzymatic antioxidants (vitamin C, alpha-tocopherol, retinol, and beta-carotene). Serum cortisol concentrations, perceived soreness, markers of muscle damage (creatine kinase (CK) and myoglobin (Mb)), and lipid peroxidation (hydroperoxides and conjugated diene lag times) were elevated to an equal extent in PS and P following exhaustive exercise before and following supplementation. The changes in running times to exhaustion from T1 to T2 in PS and P were 4.2 +/- 0.7 and -3.7 +/- 4.2%, respectively (P = 0.084). Supplementation with phosphatidylserine was not effective in attenuating the cortisol response, perceived soreness, and markers of muscle damage and lipid peroxidation following exhaustive running; however, supplementation tended to increase running time to exhaustion. Therefore, future research should be undertaken to investigate the potential ergogenic properties of this supplement.

Decrease In Eccentric Hamstring Strength During Simulated Soccer Match-play

Epidemiological research into professional soccer reports a propensity for eccentric hamstring strain injury. Furthermore, injury incidence has been observed to increase during the latter stages of match-play, attributed to fatigue. The intermittent activity profile of soccer increases the complexity of the physiological and mechanical stressors imposed on the player, and makes methodological intervention difficult. PURPOSE To develop a treadmill protocol based on the activity profile of professional soccer match-play, and thereby to simulate the physiological and mechanical demands of match-play. Subsequently to investigate the cumulative effect of soccer-specific fatigue on eccentric hamstring strength. METHODS Seven semi-professional soccer players completed the treadmill protocol, which comprised two 45 min exercise periods separated by a 15 min interval to represent half-time. A 15 min activity profile was developed, which was repeated six (6) times in total. The 15 min activity profile comprised 195 discrete bouts of exercise, producing a change in speed every 6s on average. Within this activity profile seven (7) movement speeds were included. Peak eccentric hamstring torque (T) of the dominant leg was obtained at isokinetic testing speeds of 180°s−1 (T180), 300°s−1 (T300) and 60°s−1 (T60). These measures were obtained at rest (00 min.; t00), at the end of the first half (45 min.; t45) and at the end of the second half (105 min.; t105). RESULTS ANOVA identified a significant (P<0.05) main effect for time at the fastest isokinetic trial, with T300 significantly reduced at t105 (145.88 ± 19.97 Nm) compared with t00 (205.0 ± 37.77 Nm). T300 at t45 (176.82 ± 26.12 Nm) was not significantly different to either t00 or t105, suggesting a progressive decrease in eccentric strength during the course of match-play. Whilst there was a trend for progressive reduction in eccentric hamstring strength over the course of the simulated match at testing speeds of 60°s−1 (T60 = 162.22 ± 27.36 Nm at t00; 145.82 ± 23.47 Nm at t45; 129.94 ± 20.81 at t105) and at 180°s−1 (T180 = 181.96 ± 31.86 Nm at t00; 152.60 ± 22.22 Nm at t45; 140.52 ± 18.79 Nm at t105), this decline was not significant. CONCLUSION The intermittent activity profile of soccer match-play was shown to induce a significant deterioration in eccentric hamstring strength at the fastest test speed. This reduction in eccentric strength predisposes the hamstring muscle complex to strain injury, particularly during sprinting activities, and particularly during the latter stages of match-play.

Decrease In Eccentric Hamstring Strength During Simulated Soccer Match-play

Epidemiological research into professional soccer reports a propensity for eccentric hamstring strain injury. Furthermore, injury incidence has been observed to increase during the latter stages of match-play, attributed to fatigue. The intermittent activity profile of soccer increases the complexity of the physiological and mechanical stressors imposed on the player, and makes methodological intervention difficult. PURPOSE To develop a treadmill protocol based on the activity profile of professional soccer match-play, and thereby to simulate the physiological and mechanical demands of match-play. Subsequently to investigate the cumulative effect of soccer-specific fatigue on eccentric hamstring strength. METHODS Seven semi-professional soccer players completed the treadmill protocol, which comprised two 45 min exercise periods separated by a 15 min interval to represent half-time. A 15 min activity profile was developed, which was repeated six (6) times in total. The 15 min activity profile comprised 195 discrete bouts of exercise, producing a change in speed every 6s on average. Within this activity profile seven (7) movement speeds were included. Peak eccentric hamstring torque (T) of the dominant leg was obtained at isokinetic testing speeds of 180°s−1 (T180), 300°s−1 (T300) and 60°s−1 (T60). These measures were obtained at rest (00 min.; t00), at the end of the first half (45 min.; t45) and at the end of the second half (105 min.; t105). RESULTS ANOVA identified a significant (P<0.05) main effect for time at the fastest isokinetic trial, with T300 significantly reduced at t105 (145.88 ± 19.97 Nm) compared with t00 (205.0 ± 37.77 Nm). T300 at t45 (176.82 ± 26.12 Nm) was not significantly different to either t00 or t105, suggesting a progressive decrease in eccentric strength during the course of match-play. Whilst there was a trend for progressive reduction in eccentric hamstring strength over the course of the simulated match at testing speeds of 60°s−1 (T60 = 162.22 ± 27.36 Nm at t00; 145.82 ± 23.47 Nm at t45; 129.94 ± 20.81 at t105) and at 180°s−1 (T180 = 181.96 ± 31.86 Nm at t00; 152.60 ± 22.22 Nm at t45; 140.52 ± 18.79 Nm at t105), this decline was not significant. CONCLUSION The intermittent activity profile of soccer match-play was shown to induce a significant deterioration in eccentric hamstring strength at the fastest test speed. This reduction in eccentric strength predisposes the hamstring muscle complex to strain injury, particularly during sprinting activities, and particularly during the latter stages of match-play.

Multi‐criteria optimization of ball passing in simulated soccer

AbstractSimulated soccer offers a standard real‐time environment for testing decision‐making methods for multi‐agent systems. One critical task is determining to which team‐mate the ball should be passed and the optimal point where this ball should be sent. Early methods based on enforced learning or heuristics tried to aggregate anticipated risks and pay‐offs instead of flexibly balancing them. That was because scholars were not treating ball passing as a multi‐criteria optimization problem in its classic sense. We propose a set of three criteria, tactical gain and two time balances, which should be balanced while selecting an optimal point on the field for passing the ball to. One of the advantages of this set of criteria is that they are treating direct and leading passes in the same way, thus offering a unified method for ball passing.In order to make this problem tractable, the continuous decision parameter space is replaced by a finite set of N points on the XY‐plane, which are carefully selected using some heuristics. This set is searched for non‐dominated alternatives, of which one alternative is further selected. The selection is based on the relative importance of the criteria supplied by the developer of the soccer agent. The selection method is original and uses sequential elimination of poor alternatives with respect to one criterion. Criteria are applied randomly, with the probabilities proportional to their relative importance.Experiments have shown that the multi‐criteria decision‐making algorithm is superior to its heuristic‐based counterpart. Furthermore, we suggest that it might be implemented in the RoboCup leagues dealing with physical robots. Copyright © 2006 John Wiley &amp; Sons, Ltd.

A Two-Phase Mechanism for Agent's Action Selection in Soccer Simulation

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.

An explicit investigation of implicit decision‐making processes

Using the concept of ecological rationality, different conclusions from those of Poplu, Baratgin, Mavromatis, and Ripoll in “What kind of processes underlie decision making in soccer simulation? An implicit‐memory investigation” (2003, International Journal of Sport and Exercise Psychology, 1, 390–405) can be drawn. The choice of environmental context and structure imposes constraints on possible interpretations of the obtained results. The implications of Poplu et al.’s data, new evidence, and the relationship between implicit and explicit decision‐making processes are discussed with the aim of enhancing performance in real game situations.

Non-communicative multi-robot coordination in dynamic environments

Within a group of cooperating agents the decision making of an individual agent depends on the actions of the other agents. In dynamic environments, these dependencies will change rapidly as a result of the continuously changing state. Via a context-specific decomposition of the problem into smaller subproblems, coordination graphs offer scalable solutions to the problem of multiagent decision making. In this work, we apply coordination graphs to a continuous (robotic) domain by assigning roles to the agents and then coordinating the different roles. Moreover, we demonstrate that, with some additional assumptions, an agent can predict the actions of the other agents, rendering communication superfluous. We have successfully implemented the proposed method into our UvA Trilearn simulated robot soccer team which won the RoboCup-2003 World Championship in Padova, Italy.

Teaching undergraduate software design in a liberal arts environment using RoboCup

Most large research universities include a software design or software development course as a required or elective component of an undergraduate computer science major. For various reasons, some institutions, including many liberal arts colleges and primarily undergraduate institutions, do not. In this paper, we present a software design course, tailored to undergraduate computer science students within a liberal arts environment, based on the RoboCup soccer simulation platform. We describe the course curriculum and outline its goals, which student evaluations suggest it achieved. We also outline the features of our "NewKrislet" soccer player, which provides an elementary but sufficiently functional entry point to Robocup client design.