Narrow Results

This paper outlines a framework which supports the use of multiple perspectives in system development, and provides a means for developing and applying systems design methods. The framework uses "viewpoints" to partition the system specification, the development method and the formal representations used to express the system specifications. This VOSE (viewpoint-oriented systems engineering) framework can be used to support the design of heterogeneous and composite systems. We illustrate the use of the framework with a small example drawn from composite system development and give an account of prototype automated tools based on the framework.

A hand-designed internal representation of the world cannot deal with unknown or uncontrolled environments. Motivated by human cognitive and behavioral development, this paper presents a theory, an architecture, and some experimental results for developmental robotics. By a developmental robot, we mean that the robot generates its "brain" (or "central nervous system," including the information processor and controller) through online, real-time interactions with its environment (including humans). A new Self-Aware Self-Effecting (SASE) agent concept is proposed, based on our SAIL and Dav developmental robots. The manual and autonomous development paradigms are formulated along with a theory of representation suited for autonomous development. Unlike traditional robot learning, the tasks that a developmental robot ends up learning are unknown during the programming time so that the task-specific representation must be generated and updated through real-time "living" experiences. Experimental results with SAIL and Dav developmental robots are presented, including visual attention selection, autonomous navigation, developmental speech learning, range-based obstacle avoidance, and scaffolding through transfer and chaining.

We propose a stochastic dynamic model of migration and economic aggregation in a system of employed (immobile) and unemployed (mobile) agents which respond to local wage gradients. Dependent on the local economic situation described by a production function which includes cooperative effects employed agents can become unemployed and vice versa. The spatio-temporal distribution of employed and unemployed agents is investigated both analytically and by means of stochastic computer simulations. We find the establishment of distinct economic centers out of a random initial distribution. The evolution of these centers occurs in two different stages: (i) small economic centers are formed based on the positive feedback of mutual stimulation/cooperation among the agents, (ii) some of the small centers grow at the expense of others, which finally leads to the concentration of the labor force in different extended economic regions. This crossover to large-scale production is accompanied by an increase in the unemployment rate. We observe a stable coexistence between these regions, although they exist in an internal quasistationary non-equilibrium state and still follow a stochastic eigendynamics.

For the generic specification of protocols, goals, or workflows, many approaches to agent-oriented modeling provide a concept of role. Roles abstract from the concrete agents involved in an interaction. They provide means for the evolution of agents and serve as components of agent design. Despite the widespread usage of roles in agent-oriented modeling, a systematic analysis of the different aspects and properties of this concept is still missing. In this paper, we perform such an analysis and identify requirements for a general role concept. We develop such a role concept for a modeling approach based on the UML and graph transformation systems and exemplify its use for the specification (and application) of protocols. Finally, we provide a run-time semantics for roles based on concepts from the theory of graph transformation.

We propose a stochastic dynamic model of migration and economic aggregation in a system of employed (immobile) and unemployed (mobile) agents which respond to local wage gradients. Dependent on the local economic situation, described by a production function which includes cooperative effects, employed agents can become unemployed and vice versa. The spatio-temporal distribution of employed and unemployed agents is investigated both analytically and by means of stochastic computer simulations. We find the establishment of distinct economic centers out of a random initial distribution. The evolution of these centers occurs in two different stages: (i) small economic centers are formed based on the positive feedback of mutual stimulation/cooperation among the agents, (ii) some of the small centers grow at the expense of others, which finally leads to the concentration of the labor force in different extended economic regions. This crossover to large-scale production is accompanied by an increase in the unemployment rate. We observe a stable coexistence between these regions, although they exist in an internal quasistationary non-equilibrium state and still follow a stochastic eigendynamics.

It is customary to assume that agents receive information from the environment through their sensors. It is equally customary to assume that an agent is capable of information processing and thus of computation. These two assumptions may be misleading, particularly because so much basic theoretical work relies on the concepts of information and computation. In similarity with Dennett's intentional stance, I suggest that a lot of discussions in cognitive science, neuroscience and artificial intelligence is biased by a naïve notion of computation resulting from the adoption of a computational stance. As a case study, I will focus on David Chalmers' view of computation in cognitive agents. In particular, I will challenge the thesis of computational sufficiency. I will argue that computation is no more than the ascription of an abstract model to a series of states and dynamic transitions in a physical agent. As a result, computation is akin to center of masses and other epistemic shortcuts that are insufficient to be the underpinnings of a baffling-yet-physical phenomenon like consciousness.