190 research outputs found
Towards Flexible Teamwork
Many AI researchers are today striving to build agent teams for complex,
dynamic multi-agent domains, with intended applications in arenas such as
education, training, entertainment, information integration, and collective
robotics. Unfortunately, uncertainties in these complex, dynamic domains
obstruct coherent teamwork. In particular, team members often encounter
differing, incomplete, and possibly inconsistent views of their environment.
Furthermore, team members can unexpectedly fail in fulfilling responsibilities
or discover unexpected opportunities. Highly flexible coordination and
communication is key in addressing such uncertainties. Simply fitting
individual agents with precomputed coordination plans will not do, for their
inflexibility can cause severe failures in teamwork, and their
domain-specificity hinders reusability. Our central hypothesis is that the key
to such flexibility and reusability is providing agents with general models of
teamwork. Agents exploit such models to autonomously reason about coordination
and communication, providing requisite flexibility. Furthermore, the models
enable reuse across domains, both saving implementation effort and enforcing
consistency. This article presents one general, implemented model of teamwork,
called STEAM. The basic building block of teamwork in STEAM is joint intentions
(Cohen & Levesque, 1991b); teamwork in STEAM is based on agents' building up a
(partial) hierarchy of joint intentions (this hierarchy is seen to parallel
Grosz & Kraus's partial SharedPlans, 1996). Furthermore, in STEAM, team members
monitor the team's and individual members' performance, reorganizing the team
as necessary. Finally, decision-theoretic communication selectivity in STEAM
ensures reduction in communication overheads of teamwork, with appropriate
sensitivity to the environmental conditions. This article describes STEAM's
application in three different complex domains, and presents detailed empirical
results.Comment: See http://www.jair.org/ for an online appendix and other files
accompanying this articl
Modeling human and organizational behavior using a relation-centric multi-agent system design paradigm
Today's modeling and simulation communities are being challenged to create rich, detailed models incorporating human decision-making and organizational behavior. Recent advances in distributed artificial intelligence and complex systems theory have demonstrated that such ill-defined problems can be effectively modeled with agent-based simulation techniques using multiple, autonomoous, adaptive entities. RELATE, a relation-centric design paradigm for multi-agent systems (MAS), is presented to assist developers incorporate MAS solutions into their simulations. RELATe focuses the designer on six key concepts of MAS simulations: relationships, environment, laws, agents, things, and effectors. A library of Java classes is presented which enables the user to rapidly prototype an agent-based simulation. This library utilizes the Java programming language to support cross-platform and web based designs. All Java classes and interfaces are fully documented using HTML Javadoc format. Two reference cases are provided that allow for easy code reuse and modification. Finally, an existing metworked DIS-Java-VRML simulation was modified to demonstrate the ability to utilize the RELATE library to add agents to existing applications. LCDR Kim Roddy focused on the development and refinement of the RELATE design paradigm, while LT Mike Dickson focused on the actual Java implementation. Joint work was conducted on all research and reference caseshttp://www.archive.org/details/modelinghumanorg00roddU.S. Navy (U.S.N.) author
Development of behaviors for a simulated humanoid robot
Mestrado em Engenharia de Computadores e TelemáticaControlar um robô bípede com vários graus de liberdade é um desafio que recebe a atenção de vários investigadores nas áreas da biologia, física,
electrotecnia, ciências de computadores e mecânica. Para que um humanóide possa agir em ambientes complexos, são necessários comportamentos
rápidos, estáveis e adaptáveis. Esta dissertação está centrada no desenvolvimento de comportamentos robustos para um robô humanóide
simulado, no contexto das competições de futebol robótico simulado 3D do RoboCup, para a equipa FCPortugal3D. Desenvolver tais comportamentos
exige o desenvolvimento de métodos de planeamento de trajectórias de juntas e controlo de baixo nível. Controladores PID foram implementados para o controlo de baixo nível. Para o planeamento de trajectórias, quatro métodos foram estudados. O primeiro método apresentado foi implementado antes desta dissertação e consiste numa sequência de funções degrau
que definem o ângulo desejado para cada junta durante o movimento. Um novo método baseado na interpolação de um seno foi desenvolvido e consiste em gerar uma trajectória sinusoidal durante um determinado tempo, o que resulta em transições suaves entre o ângulo efectivo e o ângulo desejado para cada junta. Um outro método que foi desenvolvido, baseado em séries parciais de Fourier, gera um padrão cíclico para cada junta, podendo ter múltiplas frequências. Com base no trabalho desenvolvido por Sven Behnke, um CPG para locomoção omnidireccional foi estudado em
detalhe e implementado. Uma linguagem de definição de comportamentos é também parte deste estudo e tem como objectivo simplificar a definição de comportamentos utilizando os vários métodos propostos. Integrando o controlo de baixo nível e os métodos de planeamento de trajectórias, vários comportamentos foram criados para permitir a uma versão simulada do humanóide NAO andar em diferentes direcções, rodar, chutar a bola, apanhar a bola (guarda-redes) e levantar do chão. Adicionalmente, a optimização e geração automática de comportamentos foi também estudada, utilizado algoritmos de optimização como o Hill Climbing e Algoritmos Genéticos.
No final, os resultados são comparados com as equipas de simulação 3D que reflectem o estado da arte. Os resultados obtidos são bons e foram capazes de ultrapassar uma das três melhores equipas simuladas do RoboCup em diversos aspectos como a velocidade a andar, a velocidade de rotação, a distância da bola depois de chutada, o tempo para apanhar a bola e o tempo para levantar do chão.
ABSTRACT: Controlling a biped robot with several degrees of freedom is a challenging task that takes the attention of several researchers in the fields of biology, physics, electronics, computer science and mechanics. For a humanoid robot to perform in complex environments, fast, stable and adaptable behaviors are required. This thesis is concerned with the development of robust behaviors
for a simulated humanoid robot, in the scope of the RoboCup 3D Simulated Soccer Competitions, for FCPortugal3D team. Developing such
robust behaviors requires the development of methods for joint trajectory planning and low-level control. PID control were implemented to achieve
low-level joint control. For trajectory planning, four methods were studied.
The first presented method was implemented before this thesis and consists of a sequence of step functions that define the target angle of each joint
during the movement. A new method based on the interpolation of a sine function was developed and consists of generating a sinusoidal shape during
some amount of time, leading to smooth transitions between the current angle and the target angle of each joint. Another method developed, based
on partial Fourier Series, generates a multi-frequency cyclic pattern for each joint. This method is very flexible and allows to completely control the angular positions and velocities of the joints. Based on the work of developed by Sven Behnke, a CPG for omnidirectional locomotion was studied in detail and implemented. A behavior definition language is also part of this study and aims at simplifying the definition of behaviors using the several proposed methods. By integrating the low-level control and the trajectory planning methods, several behaviors were created to allow a simulated version of the humanoid NAO to walk in different directions, turn, kick the ball, catch the ball (goal keeper) and get up from the ground. Furthermore, the automatic generation of gaits, through the use of optimization algorithms
such as hill climbing and genetic algorithms, was also studied and tested.
In the end, the results are compared with the state of the art teams of the RoboCup 3D simulation league. The achieved results are good and were
able to overcome one of the state of the art simulated teams of RoboCup in several aspects such as walking velocity, turning velocity, distance of the ball when kicked, time to catch the ball and the time to get up from the ground
Genetic programming for the RoboCup Rescue Simulation System
The Robocup Rescue Simulation System (RCRSS) is a dynamic system of multi-agent interaction, simulating a large-scale urban disaster scenario. Teams of rescue agents are charged with the tasks of minimizing civilian casualties and infrastructure damage while competing against limitations on time, communication, and awareness. This thesis provides the first known attempt of applying Genetic Programming (GP) to the development of behaviours necessary to perform well in the RCRSS. Specifically, this thesis studies the suitability of GP to evolve the operational behaviours required of each type of rescue agent in the RCRSS. The system developed is evaluated in terms of the consistency with which expected solutions are the target of convergence as well as by comparison to previous competition results. The results indicate that GP is capable of converging to some forms of expected behaviour, but that additional evolution in strategizing behaviours must be performed in order to become competitive. An enhancement to the standard GP algorithm is proposed which is shown to simplify the initial search space allowing evolution to occur much quicker. In addition, two forms of population are employed and compared in terms of their apparent effects on the evolution of control structures for intelligent rescue agents. The first is a single population in which each individual is comprised of three distinct trees for the respective control of three types of agents, the second is a set of three co-evolving subpopulations one for each type of agent. Multiple populations of cooperating individuals appear to achieve higher proficiencies in training, but testing on unseen instances raises the issue of overfitting
Automated generation of geometrically-precise and semantically-informed virtual geographic environnements populated with spatially-reasoning agents
La Géo-Simulation Multi-Agent (GSMA) est un paradigme de modélisation et de simulation de phénomènes dynamiques dans une variété de domaines d'applications tels que le domaine du transport, le domaine des télécommunications, le domaine environnemental, etc. La GSMA est utilisée pour étudier et analyser des phénomènes qui mettent en jeu un grand nombre d'acteurs simulés (implémentés par des agents) qui évoluent et interagissent avec une représentation explicite de l'espace qu'on appelle Environnement Géographique Virtuel (EGV). Afin de pouvoir interagir avec son environnement géographique qui peut être dynamique, complexe et étendu (à grande échelle), un agent doit d'abord disposer d'une représentation détaillée de ce dernier. Les EGV classiques se limitent généralement à une représentation géométrique du monde réel laissant de côté les informations topologiques et sémantiques qui le caractérisent. Ceci a pour conséquence d'une part de produire des simulations multi-agents non plausibles, et, d'autre part, de réduire les capacités de raisonnement spatial des agents situés. La planification de chemin est un exemple typique de raisonnement spatial dont un agent pourrait avoir besoin dans une GSMA. Les approches classiques de planification de chemin se limitent à calculer un chemin qui lie deux positions situées dans l'espace et qui soit sans obstacle. Ces approches ne prennent pas en compte les caractéristiques de l'environnement (topologiques et sémantiques), ni celles des agents (types et capacités). Les agents situés ne possèdent donc pas de moyens leur permettant d'acquérir les connaissances nécessaires sur l'environnement virtuel pour pouvoir prendre une décision spatiale informée. Pour répondre à ces limites, nous proposons une nouvelle approche pour générer automatiquement des Environnements Géographiques Virtuels Informés (EGVI) en utilisant les données fournies par les Systèmes d'Information Géographique (SIG) enrichies par des informations sémantiques pour produire des GSMA précises et plus réalistes. De plus, nous présentons un algorithme de planification hiérarchique de chemin qui tire avantage de la description enrichie et optimisée de l'EGVI pour fournir aux agents un chemin qui tient compte à la fois des caractéristiques de leur environnement virtuel et de leurs types et capacités. Finalement, nous proposons une approche pour la gestion des connaissances sur l'environnement virtuel qui vise à supporter la prise de décision informée et le raisonnement spatial des agents situés
Posicionamento estratégico nas jogadas de bola parada para a CAMBADA
Mestrado em Engenharia de Computadores e TelemáticaRobotics studies the design, construction and use of machines and or
agents designated by robots, to perform tasks with some level of complexity.
Within this scienti c domain, the coordination in multi-robot
systems has been receiving a special attention, deserving a prominent
role in the robot soccer issues. The way that each team coordinates its
robots individually and together in order to perform cooperative tasks
is the base of its strategy and in large part dictates the success of the
team in the game environment.
CAMBADA (Cooperative Autonomous Mobile roBots with Advanced
Distributed Architecture) is the robot soccer team of the University of
Aveiro, which participates in the RoboCup Middle Size League. This
team was created and developed by students and teachers belonging
to the IEETA research unit and the DETI.
The aim of this work is the improvement of the strategic positioning
in the set pieces situations, thus making it more dynamic and easily
adaptable to the di erent strategies used by the opponent teams. The
various changes made to existing algorithms, as well as new conditions
included and their applicability are described throughout this dissertation.
The work developed has been tested in the laboratory and used in
robots in the Robótica 2014 competition. Although the development
had not yet been fully completed by the date of the competition, it is
important to emphasize the increased e cacy observed in team strategy
in situations of set pieces, making the team more competitive and
able to defend and attack better.A robótica estuda o design, construção e uso de máquinas e ou agentes,
designados por robôs, para executar tarefas com algum nível de complexidade.
Dentro desta vasta área de conhecimento cientí co, a coordena
ção em sistemas multi-robô tem sido alvo de especial atenção,
merecendo um papel de destaque no domínio do futebol robótico. A
maneira como cada equipa coordena os seus robôs para o desempenho
de acções cooperativas de ne a base da sua estratégia e em grande
parte o sucesso das suas jogadas.
CAMBADA (Cooperative Autonomous Mobile roBots with Advanced
Distributed Architecture) é a equipa de futebol robótico da Universidade
de Aveiro que participa na RoboCup Middle Size League. Esta
equipa foi criada e é desenvolvida por alunos e docentes pertencentes
à unidade de investigação IEETA e ao DETI.
Este trabalho tem como principal objectivo melhorar o posicionamento
dos robôs nas jogadas de bola parada, tornando-as assim mais dinâmicas
e facilmente adaptáveis às diferentes estratégias usadas pelas outras
equipas em ambiente de jogo. As diversas alterações efectuadas aos
algoritmos já existentes, assim como as novas condições incluídas e a
sua aplicabilidade, são descritas ao longo desta dissertação.
O trabalho desenvolvido foi testado em laboratório e utilizado nos robôs
na competição Robótica 2014. Embora o desenvolvimento não estivesse
ainda completamente concluído à data da competição, é de
salientar a maior e cácia veri cada na estratégia da equipa nas situa
ções de jogadas de bola parada, tornando a equipa mais competitiva
e capaz de defender e atacar melhor
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