The Mechanics of Embodiment: A Dialogue on Embodiment and Computational Modeling

Embodied theories are increasingly challenging traditional views of cognition by arguing that conceptual representations that constitute our knowledge are grounded in sensory and motor experiences, and processed at this sensorimotor level, rather than being represented and processed abstractly in an amodal conceptual system. Given the established empirical foundation, and the relatively underspecified theories to date, many researchers are extremely interested in embodied cognition but are clamouring for more mechanistic implementations. What is needed at this stage is a push toward explicit computational models that implement sensory-motor grounding as intrinsic to cognitive processes. In this article, six authors from varying backgrounds and approaches address issues concerning the construction of embodied computational models, and illustrate what they view as the critical current and next steps toward mechanistic theories of embodiment. The first part has the form of a dialogue between two fictional characters: Ernest, the �experimenter�, and Mary, the �computational modeller�. The dialogue consists of an interactive sequence of questions, requests for clarification, challenges, and (tentative) answers, and touches the most important aspects of grounded theories that should inform computational modeling and, conversely, the impact that computational modeling could have on embodied theories. The second part of the article discusses the most important open challenges for embodied computational modelling

Proceedings of the ECCS 2005 satellite workshop: embracing complexity in design - Paris 17 November 2005

Embracing complexity in design is one of the critical issues and challenges of the 21st century. As the realization grows that design activities and artefacts display properties associated with complex adaptive systems, so grows the need to use complexity concepts and methods to understand these properties and inform the design of better artifacts. It is a great challenge because complexity science represents an epistemological and methodological swift that promises a holistic approach in the understanding and operational support of design. But design is also a major contributor in complexity research. Design science is concerned with problems that are fundamental in the sciences in general and complexity sciences in particular. For instance, design has been perceived and studied as a ubiquitous activity inherent in every human activity, as the art of generating hypotheses, as a type of experiment, or as a creative co-evolutionary process. Design science and its established approaches and practices can be a great source for advancement and innovation in complexity science. These proceedings are the result of a workshop organized as part of the activities of a UK government AHRB/EPSRC funded research cluster called Embracing Complexity in Design (www.complexityanddesign.net) and the European Conference in Complex Systems (complexsystems.lri.fr). Embracing complexity in design is one of the critical issues and challenges of the 21st century. As the realization grows that design activities and artefacts display properties associated with complex adaptive systems, so grows the need to use complexity concepts and methods to understand these properties and inform the design of better artifacts. It is a great challenge because complexity science represents an epistemological and methodological swift that promises a holistic approach in the understanding and operational support of design. But design is also a major contributor in complexity research. Design science is concerned with problems that are fundamental in the sciences in general and complexity sciences in particular. For instance, design has been perceived and studied as a ubiquitous activity inherent in every human activity, as the art of generating hypotheses, as a type of experiment, or as a creative co-evolutionary process. Design science and its established approaches and practices can be a great source for advancement and innovation in complexity science. These proceedings are the result of a workshop organized as part of the activities of a UK government AHRB/EPSRC funded research cluster called Embracing Complexity in Design (www.complexityanddesign.net) and the European Conference in Complex Systems (complexsystems.lri.fr)

Convergence Properties of Analytical Target Cascading

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/77196/1/AIAA-2002-5506-996.pd

A set-based approach for coordination of multi-level collaborative design studies

Presented in this paper is a framework for design coordination of hierarchical (multi-level) design studies. The proposed framework utilizes margin management and set-based design principles for handling the challenges associated with vertical and horizontal design coordination. The former is based on flexible constraints/margins, while the latter is handled by intersecting feasible design spaces across different teams. The framework is demonstrated with an industrial test-case from the UK ATI APPROCONE (Advanced PROduct CONcept analysis Environment) project

A Near-Optimal Decentralized Servomechanism Controller for Hierarchical Interconnected Systems

This paper is concerned with decentralized output regulation of hierarchical systems subject to input and output disturbances. It is assumed that the disturbance can be represented as the output of an autonomous LTI system with unknown initial state. The primary objective is to design a decentralized controller with the property that not only does it reject the degrading effect of the disturbance on the output (for a satisfactory steady-state performance), it also results in a small LQ cost function (implying a good transient behavior). To this end, the underlying problem is treated in two phases. In the first step, a number of modified systems are defined in terms of the original system. The problem of designing a LQ centralized controller which stabilizes all the modified systems and rejects the disturbance in the original system is considered, and it is shown that this centralized controller can be efficiently found by solving a LMI problem. In the second step, a method recently presented in the literature is exploited to decentralize the designed centralized controller. It is proved that the obtained controller satisfies the pre-determined design specifications including disturbance rejection. Simulation results elucidate the efficacy of the proposed control law

Agent-Driven Representations, Algorithms, and Metrics for Automated Organizational Design.

As cooperative multiagent systems (MASs) increase in interconnectivity, complexity, size, and longevity, coordinating the agents' reasoning and behaviors becomes increasingly difficult. One approach to address these issues is to use insights from human organizations to design structures within which the agents can more efficiently reason and interact. Generally speaking, an organization influences each agent such that, by following its respective influences, an agent can make globally-useful local decisions without having to explicitly reason about the complete joint coordination problem. For example, an organizational influence might constrain and/or inform which actions an agent performs. If these influences are well-constructed to be cohesive and correlated across the agents, then each agent is influenced into reasoning about and performing only the actions that are appropriate for its (organizationally-designated) portion of the joint coordination problem. In this dissertation, I develop an agent-driven approach to organizations, wherein the foundation for representing and reasoning about an organization stems from the needs of the agents in the MAS. I create an organizational specification language to express the possible ways in which an organization could influence the agents' decision making processes, and leverage details from those decision processes to establish quantitative, principled metrics for organizational performance based on the expected impact that an organization will have on the agents' reasoning and behaviors. Building upon my agent-driven organizational representations, I identify a strategy for automating the organizational design process~(ODP), wherein my ODP computes a quantitative description of organizational patterns and then searches through those possible patterns to identify an (approximately) optimal set of organizational influences for the MAS. Evaluating my ODP reveals that it can create organizations that both influence the MAS into effective patterns of joint policies and also streamline the agents' decision making in a coordinate manner. Finally, I use my agent-driven approach to identify characteristics of effective abstractions over organizational influences and a heuristic strategy for converging on a good abstraction.PhDComputer Science and EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/113616/1/jsleight_1.pd

A Consensus Based Decentralized State Estimation for Power Distribution Networks

This thesis presents a new Decentralized State Estimation algorithm using agents directed mainly to distribution power systems. This new algorithm solves problems that occur when one tries to estimate the state of the distribution power systems. By various reasons such as high levels of quality of service, automation capabilities and comparatively less size, those problems do not occur so frequently on the transmission systems. A consensus based static state estimation strategy for radial power distribution systems is proposed in this research. This thesis concentrates on the balanced systems.;There are buses acting as agents using which we can evaluate the local estimates of the entire system. Therefore each measurement model reduces to an under determined nonlinear system and in radial distribution systems, the state elements associated with an agent may overlap with neighboring agents. We propose a state estimation strategy, which effectively integrates the principles of local consensus and least squares technique and finally provides a decentralized solution to the radial power distribution grid. At the end of the thesis, we present the results of the application of the developed approach to a network based on a modified IEEE 13 bus test system and IEEE 33 bus Test System. The states of these systems are first estimated through centralized approach using least squares technique to compare with the proposed algorithm