171 research outputs found
Towards formal models and languages for verifiable Multi-Robot Systems
Incorrect operations of a Multi-Robot System (MRS) may not only lead to
unsatisfactory results, but can also cause economic losses and threats to
safety. These threats may not always be apparent, since they may arise as
unforeseen consequences of the interactions between elements of the system.
This call for tools and techniques that can help in providing guarantees about
MRSs behaviour. We think that, whenever possible, these guarantees should be
backed up by formal proofs to complement traditional approaches based on
testing and simulation.
We believe that tailored linguistic support to specify MRSs is a major step
towards this goal. In particular, reducing the gap between typical features of
an MRS and the level of abstraction of the linguistic primitives would simplify
both the specification of these systems and the verification of their
properties. In this work, we review different agent-oriented languages and
their features; we then consider a selection of case studies of interest and
implement them useing the surveyed languages. We also evaluate and compare
effectiveness of the proposed solution, considering, in particular, easiness of
expressing non-trivial behaviour.Comment: Changed formattin
Visual attention and swarm cognition for off-road robots
Tese de doutoramento, InformĂĄtica (Engenharia InformĂĄtica), Universidade de Lisboa, Faculdade de CiĂȘncias, 2011Esta tese aborda o problema da modelação de atenção visual no contexto de robĂŽs autĂłnomos todo-o-terreno. O objectivo de utilizar mecanismos de atenção visual Ă© o de focar a percepção nos aspectos do ambiente mais relevantes Ă tarefa do robĂŽ. Esta tese mostra que, na detecção de obstĂĄculos e de trilhos, esta capacidade promove robustez e parcimĂłnia computacional. Estas sĂŁo caracterĂsticas chave para a rapidez e eficiĂȘncia dos robĂŽs todo-o-terreno. Um dos maiores desafios na modelação de atenção visual advĂ©m da necessidade de gerir o compromisso velocidade-precisĂŁo na presença de variaçÔes de contexto ou de tarefa. Esta tese mostra que este compromisso Ă© resolvido se o processo de atenção visual for modelado como um processo auto-organizado, cuja operação Ă© modulada pelo mĂłdulo de selecção de acção, responsĂĄvel pelo controlo do robĂŽ. Ao fechar a malha entre o processo de selecção de acção e o de percepção, o Ășltimo Ă© capaz de operar apenas onde Ă© necessĂĄrio, antecipando as acçÔes do robĂŽ. Para fornecer atenção visual com propriedades auto-organizadas, este trabalho obtĂ©m inspiração da Natureza. Concretamente, os mecanismos responsĂĄveis pela capacidade que as formigas guerreiras tĂȘm de procurar alimento de forma auto-organizada, sĂŁo usados como metĂĄfora na resolução da tarefa de procurar, tambĂ©m de forma auto-organizada, obstĂĄculos e trilhos no campo visual do robĂŽ. A solução proposta nesta tese Ă© a de colocar vĂĄrios focos de atenção encoberta a operar como um enxame, atravĂ©s de interacçÔes baseadas em feromona. Este trabalho representa a primeira realização corporizada de cognição de enxame. Este Ă© um novo campo de investigação que procura descobrir os princĂpios bĂĄsicos da cognição, inspeccionando as propriedades auto-organizadas da inteligĂȘncia colectiva exibida pelos insectos sociais. Logo, esta tese contribui para a robĂłtica como disciplina de engenharia e para a robĂłtica como disciplina de modelação, capaz de suportar o estudo do comportamento adaptĂĄvel.Esta tese aborda o problema da modelação de atenção visual no contexto de robĂŽs autĂłnomos
todo-o-terreno. O objectivo de utilizar mecanismos de atenção visual é o de focar a percepção
nos aspectos do ambiente mais relevantes à tarefa do robÎ. Esta tese mostra que, na detecção de
obstĂĄculos e de trilhos, esta capacidade promove robustez e parcimĂłnia computacional. Estas
sĂŁo caracterĂsticas chave para a rapidez e eficiĂȘncia dos robĂŽs todo-o-terreno.
Um dos maiores desafios na modelação de atenção visual advém da necessidade de gerir o
compromisso velocidade-precisão na presença de variaçÔes de contexto ou de tarefa. Esta tese
mostra que este compromisso é resolvido se o processo de atenção visual for modelado como
um processo auto-organizado, cuja operação é modulada pelo módulo de selecção de acção,
responsåvel pelo controlo do robÎ. Ao fechar a malha entre o processo de selecção de acção e
o de percepção, o Ășltimo Ă© capaz de operar apenas onde Ă© necessĂĄrio, antecipando as acçÔes do
robĂŽ.
Para fornecer atenção visual com propriedades auto-organizadas, este trabalho obtém inspi-
ração da Natureza. Concretamente, os mecanismos responsåveis pela capacidade que as formi-
gas guerreiras tĂȘm de procurar alimento de forma auto-organizada, sĂŁo usados como metĂĄfora
na resolução da tarefa de procurar, também de forma auto-organizada, obståculos e trilhos no
campo visual do robÎ. A solução proposta nesta tese é a de colocar vårios focos de atenção
encoberta a operar como um enxame, através de interacçÔes baseadas em feromona.
Este trabalho representa a primeira realização corporizada de cognição de enxame. Este é
um novo campo de investigação que procura descobrir os princĂpios bĂĄsicos da cognição, ins-
peccionando as propriedades auto-organizadas da inteligĂȘncia colectiva exibida pelos insectos
sociais. Logo, esta tese contribui para a robĂłtica como disciplina de engenharia e para a robĂłtica
como disciplina de modelação, capaz de suportar o estudo do comportamento adaptĂĄvel.Fundação para a CiĂȘncia e a Tecnologia (FCT,SFRH/BD/27305/2006); Laboratory of Agent Modelling (LabMag
Artificial societies and information theory: modelling of sub system formation based on Luhmann's autopoietic theory
This thesis develops a theoretical framework for the generation of artificial societies. In particular
it shows how sub-systems emerge when the agents are able to learn and have the ability
to communicate.
This novel theoretical framework integrates the autopoietic hypothesis of human societies, formulated
originally by the German sociologist Luhmann, with concepts of Shannon's information
theory applied to adaptive learning agents.
Simulations were executed using Multi-Agent-Based Modelling (ABM), a relatively new computational
modelling paradigm involving the modelling of phenomena as dynamical systems of
interacting agents. The thesis in particular, investigates the functions and properties necessary
to reproduce the paradigm of society by using the mentioned ABM approach.
Luhmann has proposed that in society subsystems are formed to reduce uncertainty. Subsystems
can then be composed by agents with a reduced behavioural complexity. For example in
society there are people who produce goods and other who distribute them.
Both the behaviour and communication is learned by the agent and not imposed. The simulated
task is to collect food, keep it and eat it until sated. Every agent communicates its energy state
to the neighbouring agents. This results in two subsystems whereas agents in the first collect
food and in the latter steal food from others. The ratio between the number of agents that
belongs to the first system and to the second system, depends on the number of food resources.
Simulations are in accordance with Luhmann, who suggested that adaptive agents self-organise
by reducing the amount of sensory information or, equivalently, reducing the complexity of the
perceived environment from the agent's perspective. Shannon's information theorem is used
to assess the performance of the simulated learning agents. A practical measure, based on the
concept of Shannon's information
ow, is developed and applied to adaptive controllers which
use Hebbian learning, input correlation learning (ICO/ISO) and temporal difference learning.
The behavioural complexity is measured with a novel information measure, called Predictive
Performance, which is able to measure at a subjective level how good an agent is performing
a task. This is then used to quantify the social division of tasks in a social group of honest,
cooperative food foraging, communicating agents
Organisation of foraging in ants
In social insects, foraging is often cooperative, and so requires considerable organisation. In most ants, organisation is a bottom-up process where decisions taken by individuals result in emergent colony level patterns. Individuals base their decisions on their internal state, their past experience, and their environment. By depositing trail pheromones, for example, ants can alter the environment, and thus affect the behaviour of their nestmates. The development of emergent patterns depends on both how individuals affect the environment, and how they react to changes in the environment.
Chapters 4 â 9 investigate the role of trail pheromones and route memory in the ant Lasius niger. Route memories can form rapidly and be followed accurately, and when route memories and trail pheromones contradict each other, ants overwhelmingly follow route memories (chapter 4). Route memories and trail pheromones can also interact synergistically, allowing ants to forage faster without sacrificing accuracy (chapter 5). Home range markings also interact with other information sources to affect ant behaviour (chapter 6). Trail pheromones assist experienced ants when facing complex, difficult-to-learn routes (chapter 7). When facing complicated routes, ants deposit more pheromone to assist in navigation and learning (chapter 7). Deposition of trail pheromones is suppressed by ants leaving a marked path (chapter 5), strong pheromone trails (chapter 7) and trail crowding (chapter 8). Colony level âdecisionsâ can be driven by factors other than trail pheromones, such as overcrowding at a food source (chapter 9). Chapter 10 reviews the many roles of trail pheromones in ants.
Chapters 11 â 14 focus on the organisation of cooperative food retrieval. Pheidole oxyops workers arrange themselves non-randomly around items to increase transport speeds (chapter 11). Groups of ants will rotate food items to reduce drag (chapter 12). Chapters 13 and 14 encompass the ecology of cooperative transport, and how it has shaped trail pheromone recruitment in P. oxyops and Paratrechina longicornis. Lastly, chapter 15 provide a comprehensive review of cooperative transport in ants and elsewhere
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