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

Canine Justice: An Associative Account

A prominent view in contemporary political theory, the ‘associative view’, says that duties of justice are triggered by particular cooperative relations between morally significant agents, and that ‘therefore’ principles of justice apply only among fellow citizens. This view has been challenged by advocates of global justice, who point to the existence of a world-wide cooperative network to which principles of justice apply. Call this the challenge from geographical extension. In this paper, I pose a structurally similar challenge to the associative view: the challenge from species extension. This says that the existing network of cooperation extends beyond the human species, to encompass some non-human animals, particularly domesticated dogs. In light of this, if one believes that (i) certain non-human animals are morally significant (i.e. objects of moral concern), and that (ii) justice applies to fellow cooperators, one should also hold that domesticated dogs are owed justice in much the same way our human fellow citizens are. I conclude by considering the implications of this argument for the associative view, and animal-rights theory

Research and development at ORNL/CESAR towards cooperating robotic systems for hazardous environments

One of the frontiers in intelligent machine research is the understanding of how constructive cooperation among multiple autonomous agents can be effected. The effort at the Center for Engineering Systems Advanced Research (CESAR) at the Oak Ridge National Laboratory (ORNL) focuses on two problem areas: (1) cooperation by multiple mobile robots in dynamic, incompletely known environments; and (2) cooperating robotic manipulators. Particular emphasis is placed on experimental evaluation of research and developments using the CESAR robot system testbeds, including three mobile robots, and a seven-axis, kinematically redundant mobile manipulator. This paper summarizes initial results of research addressing the decoupling of position and force control for two manipulators holding a common object, and the path planning for multiple robots in a common workspace

The effect of multiple knowledge sources on learning and teaching

Current paradigms for machine-based learning and teaching tend to perform their task in isolation from a rich context of existing knowledge. In contrast, the research project presented here takes the view that bringing multiple sources of knowledge to bear is of central importance to learning in complex domains. As a consequence teaching must both take advantage of and beware of interactions between new and existing knowledge. The central process which connects learning to its context is reasoning by analogy, a primary concern of this research. In teaching, the connection is provided by the explicit use of a learning model to reason about the choice of teaching actions. In this learning paradigm, new concepts are incrementally refined and integrated into a body of expertise, rather than being evaluated against a static notion of correctness. The domain chosen for this experimentation is that of learning to solve "algebra story problems." A model of acquiring problem solving skills in this domain is described, including: representational structures for background knowledge, a problem solving architecture, learning mechanisms, and the role of analogies in applying existing problem solving abilities to novel problems. Examples of learning are given for representative instances of algebra story problems. After relating our views to the psychological literature, we outline the design of a teaching system. Finally, we insist on the interdependence of learning and teaching and on the synergistic effects of conducting both research efforts in parallel

Analysing practice in preservice mathematics teacher education

This paper presents the case of a yearlong course based on fieldwork activities provided to secondary school mathematics preservice teachers, just before their student teaching practicum. The activities are a first experience in investigating professional practice—some concern the school as a whole, while others focus on the mathematics class. Using a qualitative and collaborative methodology, we discuss the implications of this work for preservice teachers’ education. We argue that such fieldwork activities may help prospective teachers in developing a professional discourse and in assuming a professional identity, acquiring new ways of expressing new educational ideas and assuming a new point of view about educational phenomena