Multiobjective optimization for interwoven systems

In practical situations, complex systems are often composed of subsystems or subproblems with single or multiple objectives. These subsystems focus on different aspects of the overall system, but they often have strong interactions with each other and they are usually not sequentially ordered or obviously decomposable. Thus, the individual solutions of subproblems do not generally induce a solution for the overall system. Here, we strive to identify “re‐composition architectures” of such “interwoven” systems. Our intention is to connect the subsystems adequately, analyze the resulting performance, model/solve the overall system, and improve the overall solution instead of just solving each subsystem separately. We review recent developments in this field and discuss modeling and solution paradigms in a general and unified framework using the example of an interwoven system consisting of two interacting subsystems.     

On Finitely-Valued Inference Systems

A proof-theoretical analysis of finite-valuedness in the domain of cumulative inference systems is presented.     

Deontic Interpreted Systems

We investigate an extension of the formalism of interpreted systems by Halpern and colleagues to model the correct behaviour of agents. The semantical model allows for the representation and reasoning about states of correct and incorrect functioning behaviour of the agents, and of the system as a whole. We axiomatise this semantic class by mapping it into a suitable class of Kripke models. The resulting logic, KD45_n ^i-j, is a stronger version of KD, the system often referred to as Standard Deontic Logic. We extend this formal framework to include the standard epistemic notions defined on interpreted systems, and introduce a new doubly-indexed operator representing the knowledge that an agent would have if it operates under the assumption that a group of agents is functioning correctly. We discuss these issues both theoretically and in terms of applications, and present further directions of work.     

Editor’s introduction: Innovative dynamical approaches to cognitive systems

This Editor’s Introduction to the Cognitive Systems Research special issue, “Innovative Dynamical Approaches to Cognitive Systems,” has three aims: First, the background and motivation for the topic are stated. Second, overviews of the contributing papers are presented. Third, based on the papers, speculations on future directions in dynamical approaches to the investigation of cognitive systems are presented. Here, the focus is on concepts, data analysis methods, and computational modeling.     

Systems Theory and Family Therapy: From a Critique on Systems Theory to a Theory on System Change

Some system therapists reject the systemic view for various reasons, often related to violence, victimisation and power. This critique is based on an outdated narrow and incomplete knowledge of linear systems theory. A better understanding of these linear systems theories and of systems levels of organisation already answers much of the critique, but does not explain change. For the latter, a theory of how systems change is necessary for systems therapy in general and family therapy in particular. Modern dynamic systems and chaos theory are most useful to understand change, chaos, history, unpredictability and flexibility.     

心理学研究方法的系统分析与体系重构

心理学研究方法在心理学的发展中占有特别重要的地位。当前,心理学研究方法已经成为心理学中的一门重要学科,相关论文和教材很多。本文首先对心理学研究方法的发展进行了简要概述,重点指出了心理学研究方法研究中存在的重大问题,在此基础上,我们对心理学研究方法进行了系统分析,并构建了心理学研究方法的新体系。     

Applying linear systems analysis to dynamic behavior

In this paper we present an abbreviated discussion of the linear systems analysis in the time domain. We then consider the qualitative character of the behavioral dynamics predicted using the linear form of the analysis. The analysis is then extended to a second-order form. We illustrate some relevant new features introduced by the second-order form with a special case example.     

Can novice drivers be motivated to use a smartphone based app that monitors their behavior?

Encouraging young drivers to use driving feedback systems (referred here as GreenBoxes) is a challenge. Prior research and experience indicated that mainly due to insufficient motivation, adoption of GreenBoxes is minimal. Research also demonstrated that once feedback from GreenBoxes is provided to young drivers and their parents, the frequency of risky driving behavior is reduced.This study investigated the possible benefits of providing group incentives to encourage usage of GreenBoxes among young drivers. The specific GreenBox used in this study was a smartphone app that needed to be initiated at the beginning of each trip. Once initiated it monitors driving behavior in terms of G-force events, provides score and feedback, and shares the driving information with a pre-defined sponsor.This study builds and expands on a previous study by making the duration of the experiment longer, and by allowing participants to recruit their friends in order to help the group win its rewards.Despite of the more challenging scheme needed to gain rewards, the results obtained repeat the success of the previous study: all eligible participants downloaded the app and used it to win the rewards for the group. Additionally, friends were recruited by participants and used the app to help the group win rewards (without getting any personal rewards for themselves). However, once all the pre-specified rewards were achieved within the allotted time period, the young drivers stopped using the app.This study confirms again that barriers to adoption of GreenBox app among young drivers can be overcome by choosing low-cost suitable group incentive schemes.     

Substantive and procedural norms in normative multiagent systems

Procedural norms are instrumental norms addressed to agents playing a role in the normative system, for example to motivate these role playing agents to recognize violations or to apply sanctions. Procedural norms have first been discussed in law, where they address legal practitioners such as legislators, lawyers and policemen, but they are discussed now too in normative multiagent systems to motivate software agents. Procedural norms aim to achieve the social order specified using regulative norms like obligations and permissions, and constitutive norms like counts-as obligations. In this paper we formalize procedural, regulative and constitutive norms using input/output logic enriched with an agent ontology and an abstraction hierarchy. We show how our formalization explains Castelfranchi's notion of mutual empowerment, stating that not only the agents playing a role in a normative system are empowered by the normative system, but the normative system itself is also empowered by the agents playing a role in it. In our terminology, the agents are not only institutionally empowered, but they are also delegated normative goals from the system. Together, institutional empowerment and normative goal delegation constitute a mechanism which we call delegation of power, where agents acting on behalf of the normative system become in charge of recognizing which institutional facts follow from brute facts.     

Value systems for developmental cognitive robotics: A survey

This paper surveys value systems for developmental cognitive robotics. A value system permits a biological brain to increase the likelihood of neural responses to selected external phenomena. Many machine learning algorithms capture the essence of this learning process. However, computational value systems aim not only to support learning, but also autonomous attention focus to direct learning. This combination of unsupervised attention focus and learning aims to address the grand challenge of autonomous mental development for machines. This survey examines existing value systems for developmental cognitive robotics in this context. We examine the definitions of value used—including recent pioneering work in intrinsic motivation as value—as well as initialisation strategies for innate values, update strategies for acquired value and the data structures used for storing value. We examine the extent to which existing value systems support attention focus, learning and prediction in an unsupervised setting. The types of robots and applications in which these value systems are used are also examined, as well as the ways that these applications are evaluated. Finally, we study the strengths and limitations of current value systems for developmental cognitive robots and conclude with a set of research challenges for this field.     

An O(n log n)-Space Decision Procedure for the Relevance Logic B+

In previous work we gave a new proof-theoretical method for establishing upper-bounds on the space complexity of the provability problem of modal and other propositional non-classical logics. Here we extend and refine these results to give an O(n log n)-space decision procedure for the basic positive relevance logic B⁺. We compute this upper-bound by first giving a sound and complete, cut-free, labelled sequent system for B⁺, and then establishing bounds on the application of the rules of this system.     

Multi-Agent neurocognitive models of semantics of spatial localization of events

The purpose of the study is to develop a learning system for internal representation of the events localization space to realize orientation and navigation of autonomous mobile systems. The task of the research is the development of simulation models of the semantics of the event localization space based on multi-agent neurocognitive architectures. The paper proves that the multi-agent neurocognitive architecture is an effective formalism for describing the semantics of the spatial localization of events. Main theoretical foundations have been developed for the simulation of spatial relations using the so-called multi-agent facts, consisting of software agents-concepts, reflecting semantic categories corresponding to parts of speech. It is shown that locative software agents that describe the spatial location of objects and events, forming homogeneous connections, compose the so-called field locations. The latter describes a holistic view of the intellectual agent about the environment. The paper defines conceptual foundations of multi-agent modeling of the semantics of subjective reflexive mapping of the interaction between real objects, space and time.     

Visual interaction: models, systems, prototypes. The Pictorial Computing Laboratory at the University of Rome “La Sapienza”

This paper reports on the research activities performed by the Pictorial Computing Laboratory at the University of Rome, La Sapienza, during the last 5 years. Such work, essentially is based on the study of humancomputer interaction, spans from metamodels of interaction down to prototypes of interactive systems for both synchronous multimedia communication and groupwork, annotation systems for web pages, also encompassing theoretical and practical issues of visual languages and environments also including pattern recognition algorithms. Some applications are also considered like e-learning and collaborative work.     

How does a word become a message? An illustration on a developmental time-scale

Recent changes in views on cognition underscore its embodied, situated and distributed character. These changes are compatible with the conceptual framework of ecological psychology. However for ecological psychology to propose explanations for a broad range of cognitive phenomena, including language, it needs an account of how to link the dynamics of coupling between the organism and the environment with the apparent symbolicity of informational structures. In this paper it is proposed that a theory of information in biological systems, advocated by Howard Pattee, may help forge this link. By treating informational structures as constraints on dynamics this approach helps to identify which processes, in which systems and on what time-scales are needed for structures to ‘become messages’. I will illustrate how these processes might work on developmental time-scale in the domain of language, building on the work by Edward Reed (1995, 1996) and extending it using the view of linguistic structures as constraints.     

系统生物医学与中医现代化

中医的阴阳平衡理论与辨证施治的临床实践与系统生物学追求的整体论和系统论不谋而合,两者相结合而产生的生物系统医学体现了我国学者在医学研究中的创新之路,其中代谢组学的研究为中医药的现代化和国际化开辟了新的方向。第一届系统生物医学上海论坛——代谢组学与中医药国际化研讨会的召开标志着我国传统医学走上了新的发展道路。     

REFLECTIONS: EDUCATION AND OUR SHARED FUTURE

Based on a comparative study, this paper highlights and analyses commonalities and differences between an Oriental systems approach, WSR, and two Western counterparts, TOP and MMD. It is suggested that cultural differences among systems approaches might probably have been overshadowed by both commonalities between Western and Eastern traditions and differences within the same cultural tradition. It will be further proposed that by being more consciously open to and learning from each other, systems approaches in the East and the West may have more to offer for dealing with the complexity which confronts humankind.     

A transactional systems model of autism services

There has been an escalation in the number of children identified with autism spectrum disorders in recent years. To increase the likelihood that treatments for these children are effective, interventions should be derived from sound theory and research evidence. Absent this supportive foundation, intervention programs could be inconsequential if not harmful. Although atypical, the development of children with autism should be considered initially from the perspective of the same variables that affect the development of typical children. In addition, the developmental deviations that characterize autism must be considered when developing intervention programs. Behavioral systems models describe both typical and atypical development and emphasize dynamic multidirectional person-environment transactions. The environment is viewed as having multiple levels, from the individuals with autism themselves, to larger societal and cultural levels. Behavioral systems models of human development can be generalized to a transactional systems model of services for children with autism. This model is the foundational theoretical position of the Southern Illinois University Center for Autism Spectrum Disorders. The center's programs are described to illustrate the application of the model to multiple levels of the social ecology.     

Systems Thinking for Knowledge

The capacity to engage in systems thinking is often viewed as being a product of being able to understand complex systems due to one's facility in mastering systems theories, methods, and being able to adeptly reason. Relatively little attention is paid in the systems literature to the processes of learning from experience and creating knowledge as a direct consequence of individuals engaging systems thinking itself over time. In fact, the potential efficacy of systems thinking to improve performance normally seen as only contingent on a priori knowledge, rather than knowledge created via learning from experience. Such newly create knowledge often results from engaging in modeling efforts and systemic forms of inquiry. This article proposes a model for creating new knowledge by coupling systems modeling with a pragmatic approach to knowledge-creation. This approach is based on a foundation of the pragmatic concepts first proposed by the American philosopher/scientist Charles Sanders Peirce over a century ago. This model offers systems practitioners a framework to engage in knowledge-intensive systems thinking (KIST) for addressing complex problematic issues.     

Discovery in complex adaptive systems

The distinction between ontological ground-truth phenomena and epistemic measurements of those phenomena is discussed and analyzed in the context of complex cognitive systems research. A common style of computational simulation is identified as a Dissect-the-Simulation motif. In this style, a model of cognition is designed and when it generally mimics some cognitive behavior, its own ontic processes (which are fully accessible because it is a simulation) are proposed as potential ontic processes inside actual human cognition. I propose here a second style of modeling, which might be called Measure-the-Simulation. In this style, simulated versions of coarse-grained epistemic measurements are performed on the model with the intent of discovering how those epistemic measurements themselves may transform the actual ontic data, and thus induce a variety of mis-categorizations of phenomena. When our epistemic measurements are better understood, such mis-categorizations can perhaps be avoided. As a proof of concept, Conway’s Game of Life is analyzed and measured with two different types of coarse-grained epistemic measures. Dramatic differences are identified in how a binary coarse-graining, versus a graded coarse-graining, transforms the discovery process for activity patterns on the lattice of this cellular automaton.