40,128 research outputs found
Distributed, cooperating knowledge-based systems
Some current research in the development and application of distributed, cooperating knowledge-based systems technology is addressed. The focus of the current research is the spacecraft ground operations environment. The underlying hypothesis is that, because of the increasing size, complexity, and cost of planned systems, conventional procedural approaches to the architecture of automated systems will give way to a more comprehensive knowledge-based approach. A hallmark of these future systems will be the integration of multiple knowledge-based agents which understand the operational goals of the system and cooperate with each other and the humans in the loop to attain the goals. The current work includes the development of a reference model for knowledge-base management, the development of a formal model of cooperating knowledge-based agents, the use of testbed for prototyping and evaluating various knowledge-based concepts, and beginning work on the establishment of an object-oriented model of an intelligent end-to-end (spacecraft to user) system. An introductory discussion of these activities is presented, the major concepts and principles being investigated are highlighted, and their potential use in other application domains is indicated
Cooperation Enforcement and Collusion Resistance in Repeated Public Goods Games
Enforcing cooperation among substantial agents is one of the main objectives
for multi-agent systems. However, due to the existence of inherent social
dilemmas in many scenarios, the free-rider problem may arise during agents'
long-run interactions and things become even severer when self-interested
agents work in collusion with each other to get extra benefits. It is commonly
accepted that in such social dilemmas, there exists no simple strategy for an
agent whereby she can simultaneously manipulate on the utility of each of her
opponents and further promote mutual cooperation among all agents. Here, we
show that such strategies do exist. Under the conventional repeated public
goods game, we novelly identify them and find that, when confronted with such
strategies, a single opponent can maximize his utility only via global
cooperation and any colluding alliance cannot get the upper hand. Since a full
cooperation is individually optimal for any single opponent, a stable
cooperation among all players can be achieved. Moreover, we experimentally show
that these strategies can still promote cooperation even when the opponents are
both self-learning and collusive
Artificial Intelligence and Systems Theory: Applied to Cooperative Robots
This paper describes an approach to the design of a population of cooperative
robots based on concepts borrowed from Systems Theory and Artificial
Intelligence. The research has been developed under the SocRob project, carried
out by the Intelligent Systems Laboratory at the Institute for Systems and
Robotics - Instituto Superior Tecnico (ISR/IST) in Lisbon. The acronym of the
project stands both for "Society of Robots" and "Soccer Robots", the case study
where we are testing our population of robots. Designing soccer robots is a
very challenging problem, where the robots must act not only to shoot a ball
towards the goal, but also to detect and avoid static (walls, stopped robots)
and dynamic (moving robots) obstacles. Furthermore, they must cooperate to
defeat an opposing team. Our past and current research in soccer robotics
includes cooperative sensor fusion for world modeling, object recognition and
tracking, robot navigation, multi-robot distributed task planning and
coordination, including cooperative reinforcement learning in cooperative and
adversarial environments, and behavior-based architectures for real time task
execution of cooperating robot teams
The Organization and Control of an Evolving Interdependent Population
Starting with Darwin, biologists have asked how populations evolve from a low
fitness state that is evolutionarily stable to a high fitness state that is
not. Specifically of interest is the emergence of cooperation and
multicellularity where the fitness of individuals often appears in conflict
with that of the population. Theories of social evolution and evolutionary game
theory have produced a number of fruitful results employing two-state two-body
frameworks. In this study we depart from this tradition and instead consider a
multi-player, multi-state evolutionary game, in which the fitness of an agent
is determined by its relationship to an arbitrary number of other agents. We
show that populations organize themselves in one of four distinct phases of
interdependence depending on one parameter, selection strength. Some of these
phases involve the formation of specialized large-scale structures. We then
describe how the evolution of independence can be manipulated through various
external perturbations.Comment: To download simulation code cf. article in Proceedings of the Royal
Society, Interfac
- …