186 research outputs found
Automata for infinite argumentation structures
The theory of abstract argumentation frameworks (afs) has, in the main, focused on finite structures, though there are many significant contexts where argumentation can be regarded as a process involving infinite objects. To address this limitation, in this paper we propose a novel approach for describing infinite afs using tools from formal language theory. In particular, the possibly infinite set of arguments is specified through the language recognized by a deterministic finite automaton while a suitable formalism, called attack expression, is introduced to describe the relation of attack between arguments. The proposed approach is shown to satisfy some desirable properties which cannot be achieved through other “naive” uses of formal languages. In particular, the approach is shown to be expressive enough to capture (besides any arbitrary finite structure) a large variety of infinite afs including two major examples from previous literature and two sample cases from the domains of multi-agent negotiation and ambient intelligence. On the computational side, we show that several decision and construction problems which are known to be polynomial time solvable in finite afs are decidable in the context of the proposed formalism and we provide the relevant algorithms. Moreover we obtain additional results concerning the case of finitaryafs
Defeasible Argumentation for Cooperative Multi-Agent Planning
Tesis por compendio[EN] Multi-Agent Systems (MAS), Argumentation and Automated Planning are three lines of investigations within the field of Artificial Intelligence (AI) that have been extensively studied over the last years. A MAS is a system composed of multiple intelligent agents that interact with each other and it is used to solve problems whose solution requires the presence of various functional and autonomous entities. Multi-agent systems can be used to solve problems that are difficult or impossible to resolve for an individual agent. On the other hand, Argumentation refers to the construction and subsequent exchange (iteratively) of arguments between a group of agents, with the aim of arguing for or against a particular proposal. Regarding Automated Planning, given an initial state of the world, a goal to achieve, and a set of possible actions, the goal is to build programs that can automatically calculate a plan to reach the final state from the initial state.
The main objective of this thesis is to propose a model that combines and integrates these three research lines. More specifically, we consider a MAS as a team of agents with planning and argumentation capabilities. In that sense, given a planning problem with a set of objectives, (cooperative) agents jointly construct a plan to satisfy the objectives of the problem while they defeasibly reason about the environmental conditions so as to provide a stronger guarantee of success of the plan at execution time. Therefore, the goal is to use the planning knowledge to build a plan while agents beliefs about the impact of unexpected environmental conditions is used to select the plan which is less likely to fail at execution time. Thus, the system is intended to return collaborative plans that are more robust and adapted to the circumstances of the execution environment.
In this thesis, we designed, built and evaluated a model of argumentation based on defeasible reasoning for planning cooperative multi-agent system. The designed system is independent of the domain, thus demonstrating the ability to solve problems in different application contexts. Specifically, the system has been tested in context sensitive domains such as Ambient Intelligence as well as with problems used in the International Planning Competitions.[ES] Dentro de la Inteligencia Artificial (IA), existen tres ramas que han sido ampliamente estudiadas en los últimos años: Sistemas Multi-Agente (SMA), Argumentación y Planificación Automática. Un SMA es un sistema compuesto por múltiples agentes inteligentes que interactúan entre sí y se utilizan para resolver problemas cuya solución requiere la presencia de diversas entidades funcionales y autónomas. Los sistemas multiagente pueden ser utilizados para resolver problemas que son difíciles o imposibles de resolver para un agente individual. Por otra parte, la Argumentación consiste en la construcción y posterior intercambio (iterativamente) de argumentos entre un conjunto de agentes, con el objetivo de razonar a favor o en contra de una determinada propuesta. Con respecto a la Planificación Automática, dado un estado inicial del mundo, un objetivo a alcanzar, y un conjunto de acciones posibles, el objetivo es construir programas capaces de calcular de forma automática un plan que permita alcanzar el estado final a partir del estado inicial.
El principal objetivo de esta tesis es proponer un modelo que combine e integre las tres líneas anteriores. Más específicamente, nosotros consideramos un SMA como un equipo de agentes con capacidades de planificación y argumentación. En ese sentido, dado un problema de planificación con un conjunto de objetivos, los agentes (cooperativos) construyen conjuntamente un plan para resolver los objetivos del problema y, al mismo tiempo, razonan sobre la viabilidad de los planes, utilizando como herramienta de diálogo la Argumentación. Por tanto, el objetivo no es sólo obtener automáticamente un plan solución generado de forma colaborativa entre los agentes, sino también utilizar las creencias de los agentes sobre la información del contexto para razonar acerca de la viabilidad de los planes en su futura etapa de ejecución. De esta forma, se pretende que el sistema sea capaz de devolver planes colaborativos más robustos y adaptados a las circunstancias del entorno de ejecución.
En esta tesis se diseña, construye y evalúa un modelo de argumentación basado en razonamiento defeasible para un sistema de planificación cooperativa multiagente. El sistema diseñado es independiente del dominio, demostrando así la capacidad de resolver problemas en diferentes contextos de aplicación. Concretamente el sistema se ha evaluado en dominios sensibles al contexto como es la Inteligencia Ambiental y en problemas de las competiciones internacionales de planificación.[CA] Dins de la intel·ligència artificial (IA), hi han tres branques que han sigut àmpliament estudiades en els últims anys: Sistemes Multi-Agent (SMA), Argumentació i Planificació Automàtica. Un SMA es un sistema compost per múltiples agents intel·ligents que interactúen entre si i s'utilitzen per a resoldre problemas la solución dels quals requereix la presència de diverses entitats funcionals i autònomes. Els sistemes multiagente poden ser utilitzats per a resoldre problemes que són difícils o impossibles de resoldre per a un agent individual. D'altra banda, l'Argumentació consistiex en la construcció i posterior intercanvi (iterativament) d'arguments entre un conjunt d'agents, amb l'objectiu de raonar a favor o en contra d'una determinada proposta. Respecte a la Planificació Automàtica, donat un estat inicial del món, un objectiu a aconseguir, i un conjunt d'accions possibles, l'objectiu és construir programes capaços de calcular de forma automàtica un pla que permeta aconseguir l'estat final a partir de l'estat inicial.
El principal objectiu d'aquesta tesi és proposar un model que combine i integre les tres línies anteriors. Més específicament, nosaltres considerem un SMA com un equip d'agents amb capacitats de planificació i argumentació. En aquest sentit, donat un problema de planificació amb un conjunt d'objectius, els agents (cooperatius) construeixen conjuntament un pla per a resoldre els objectius del problema i, al mateix temps, raonen sobre la viabilitat dels plans, utilitzant com a ferramenta de diàleg l'Argumentació. Per tant, l'objectiu no és només obtindre automàticament un pla solució generat de forma col·laborativa entre els agents, sinó també utilitzar les creences dels agents sobre la informació del context per a raonar sobre la viabilitat dels plans en la seua futura etapa d'execució. D'aquesta manera, es pretén que el sistema siga capaç de tornar plans col·laboratius més robustos i adaptats a les circumstàncies de l'entorn d'execució.
En aquesta tesi es dissenya, construeix i avalua un model d'argumentació basat en raonament defeasible per a un sistema de planificació cooperativa multiagent. El sistema dissenyat és independent del domini, demostrant així la capacitat de resoldre problemes en diferents contextos d'aplicació. Concretament el sistema s'ha avaluat en dominis sensibles al context com és la inte·ligència Ambiental i en problemes de les competicions internacionals de planificació.Pajares Ferrando, S. (2016). Defeasible Argumentation for Cooperative Multi-Agent Planning [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/60159TESISCompendi
List Cultures
We live in an age of lists, from magazine features to online clickbait. This book situates the list in a long tradition, asking key questions about the list as a cultural and communicative form. What, Liam Cole Young asks, can this seemingly innocuous form tell us about historical and contemporary media environments and logistical networks? Connecting German theories of cultural techniques to Anglo-American approaches that address similar issues, List Cultures makes a major contribution to debates about New Materialism and the post-human turn
Proceedings of the 11th Workshop on Nonmonotonic Reasoning
These are the proceedings of the 11th Nonmonotonic Reasoning Workshop. The aim of this series is to bring together active researchers in the broad area of nonmonotonic reasoning, including belief revision, reasoning about actions, planning, logic programming, argumentation, causality, probabilistic and possibilistic approaches to KR, and other related topics. As part of the program of the 11th workshop, we have assessed the status of the field and discussed issues such as: Significant recent achievements in the theory and automation of NMR; Critical short and long term goals for NMR; Emerging new research directions in NMR; Practical applications of NMR; Significance of NMR to knowledge representation and AI in general
Mixing Dyadic and Deliberative Opinion Dynamics in an Agent-Based Model of Group Decision-Making
International audienceIn this article, we propose an agent-based model of opinion diffusion and voting where influence among individuals and deliberation in a group are mixed. The model is inspired from social modeling, as it describes an iterative process of collective decision-making that repeats a series of interindividual influences and collective deliberation steps, and studies the evolution of opinions and decisions in a group. It also aims at founding a comprehensive model to describe collective decision-making as a combination of two different paradigms: argumentation theory and ABM-influence models, which are not obvious to combine as a formal link between them is required. In our model, we find that deliberation, through the exchange of arguments, reduces the variance of opinions and the proportion of extremists in a population as long as not too much deliberation takes place in the decision processes. Additionally, if we define the correct collective decisions in the system in terms of the arguments that should be accepted, allowing for more deliberation favors convergence towards the correct decisions
Digital Humanities and Digital Media: Conversations on Politics, Culture, Aesthetics and Literacy
There is no doubt that we live in exciting times: Ours is the age of many ‘silent revolutions’ triggered by startups and research labs of big IT companies; revolutions that quietly and profoundly alter the world we live in. Another ten or five years, and self-tracking will be as normal and inevitable as having a Facebook account or a mobile phone. Our bodies, hooked to wearable devices sitting directly at or beneath the skin, will constantly transmit data to the big aggregation in the cloud. Permanent recording and automatic sharing will provide unabridged memory, both shareable and analyzable. The digitization of everything will allow for comprehensive quantification; predictive analytics and algorithmic regulation will prove themselves effective and indispensable ways to govern modern mass society. Given such prospects, it is neither too early to speculate on the possible futures of digital media nor too soon to remember how we expected it to develop ten, or twenty years ago. The observations shared in this book take the form of conversations about digital media and culture centered around four distinct thematic fields: politics and government, algorithm and censorship, art and aesthetics, as well as media literacy and education. Among the keywords discussed are: data mining, algorithmic regulation, sharing culture, filter bubble, distant reading, power browsing, deep attention, transparent reader, interactive art, participatory culture. The interviewees (mostly from the US, but also from France, Brazil, and Denmark) were given a set of common questions as well specific inquiries tailored to their individual areas of interest and expertise. As a result, the book both identifies different takes on the same issues and enables a diversity of perspectives when it comes to the interviewees’ particular concerns.
Among the questions offered to everybody were: What is your favored neologism of digital media culture? If you could go back in history of new media and digital culture in order to prevent something from happening or somebody from doing something, what or who would it be? If you were a minister of education, what would you do about media literacy? What is the economic and political force of personalization and transparency in digital media and what is its personal and cultural cost? Other recurrent questions address the relationship between cyberspace and government, the Googlization, quantification and customization of everything, and the culture of sharing and transparency. The section on art and aesthetics evaluates the former hopes for hypertext and hyperfiction, the political facet of digital art, the transition from the “passive” to “active” and from “social” to “transparent reading”; the section on media literacy discusses the loss of deep reading, the prospect of “distant reading” and “algorithmic criticism” as well as the response of the university to the upheaval of new media and the expectations or misgivings towards the rise of the Digital Humanities
Chiasmus: a phenomenon of language, body and perception
The term chiasmus and all its many variants describe a phenomenon of language, body and perception. As a syntactic-rhetorical device, the usage of which is culturally diffuse, chiasmus involves a re-ordering of elements in a sentence to produce an A-B-B-A pattern. An example of this is the well-known saying falsely attributed to Hippocrates: “Let thy food be thy medicine and medicine be thy food.” As a symbol, chiasmus describes a pattern with intersecting lines, the most simplistic form of which is the X. Chiasm, in the work of Maurice Merleau-Ponty, refers to a phenomenon of body and mind. Insofar as it is used in the latter part of this work, chiasm refers to how the body and brain negotiate motor function, touch and perception: the right hemisphere of the brain corresponds with movement and function in the left side of the body, and the left hemisphere of the brain corresponds to movement and function in the right side of the body. All chiastic forms involve an intersection or crossing of the elements—whether syntactical or anatomical.
The first chapter of the thesis is a literature review entitled, “Chiastic Studies and Typology,” which gives an overview of a few in-depth studies on chiasmus and of chiastic types that have been identified in semiotics and at the syntactical level. The second chapter of the thesis, “Chiastic Forms and Figures: Truths, Logic and Cross-Linguistic Usage” examines chiasmus as a semiotic and syntactic phenomenon. Part of the discussion considers whether and how chiasmus as a semiotic phenomenon is not only a symbol of self, but also a symbol of the person’s truthfulness or trustworthiness. Proceeding on, this section transitions into a broader reflection on how chiasmus overlaps with truth-functional logic and is an aspect of systematicity in language.
Focusing specifically on a sub-type of chiasmus, antimetabole, this section highlights 80 different examples, in 28 different languages and family groups. Antimetabole is characterized by precise reversals of the sentence elements: “Let thy food be thy medicine and medicine be thy food” entails a repetition and reversal of the elements medicine and food. This phrase would still be chiastic if a synonym for food was used, but it would not be an example of antimetabole. The identified examples of antimetabole fit into eight types:
1) Equalization: AB equates to or is the same as BA
2) Part-whole: A is part of B, and B is part of A
3) Exclusion: A excludes B, and B excludes A
4) Dissociation: A dissociates from B, B dissociates from A
5) Combination: A and B, B and A; the elements are grouped together
6) Comparison: A and B are better than B and A; or A and B are worse than B and A
7) One Way Effects: A affects B, but B does not affect A; or A does not affect B, but B affects A
8) Multiple Effects: A affects B, and B affects A; or A affects B and B affects A;
can also include more elaborate reversals with repeating C, D, E elements
The third chapter of the work, “Merleau-Ponty’s Chiasm: a Theory of Perception” concerns Maurice Merleau-Ponty’s text The Visible and the Invisible, in which he develops chiasm as a concept. This is an interpretation of his text that argues that the chiasm is a five-fold bodily relation, referring to:
1) Its role in connecting the visible with the invisible – or the perceptual with mental phenomena
2) The way the two eyes work together to produce one perceptual experience
3) The experience of touch other things and touching oneself
4) A linguistic and meaning-making process, in which meaning is constantly in flux
5) The social dynamic, or interactivity between One and Other
The fourth chapter, “Models of the Brain: Metaphors, Architectures and Chiastic Applications” argues that the chiasm has usefulness in describing perception and activities of the brain. Beginning with a criticism of metaphors of the brain which have been influential in defining approaches to artificial intelligence, this chapter reveals the shortcomings of calling the brain a hierarchy, and the related notion that the brain is either a top-down or bottom-up architecture. It also challenges presently held views on how information is stored in a brain. Each sub-section accomplishes this by examining a different approach, including:
1) Representational Theory of Mind and its corresponding logic-based efforts to produce an artificially intelligent computer
2) Connectionism and one of its promising descendants in deep learning, specifically the convolutional neural network underlying SPAUN (Semantic Pointer Architecture Unified Network); and
3) Bayesian approaches to mind, which found momentum alongside linear predictive coding, and Hidden Markov models.
To complete this analysis is a more intensive argument that the architecture of the biological human brain is chiastic, rather than strictly top-down or bottom-up. The final part of this chapter draws on the philosophy of Maurice Merleau-Ponty, along with a body of research on the brain and bodily hemispheres. It demonstrates why scholars and engineers in artificial intelligence would be remiss to overlook the chiasm—both in developing theories of perception, and when it comes to making practical design choices in building more humanlike artificial intelligence.
The last chapter in the thesis “Embodied X Figures and Forms of Thought” is intended to be a companion piece or footnote to the first. It is a review of Pelkey’s 2017 book, The Semiotics of X: Chiasmus, Cognition, and Extreme Body Memory. This review was previously published in Semiotica and is included here to provide further useful background
Collective intelligence: creating a prosperous world at peace
XXXII, 612 p. ; 24 cmLibro ElectrónicoEn este documento se plantea un tema de interes general mas como lo es especificamente el tema de la evolucion de la sociedad en materia de industria y crecimiento de las actividades humanas en el aspecto de desarrollo de la creatividad enfocada a los mercadosedited by Mark Tovey ; foreword by Yochai Benkler (re-mixed by Hassan Masum) ; prefaces by Thomas Malone, Tom Atlee & Pierre Levy ; afterword by Paul Martin & Thomas Homer-Dixon.The era of collective intelligence has begun in earnest. While others have written about the wisdom of crowds, an army of Davids, and smart mobs, this collection of essays for the first time brings together fifty-five pioneers in the emerging discipline of collective intelligence. They provide a base of tools for connecting people, producing high-functioning teams, collaborating at multiple scales, and encouraging effective peer-production. Emerging models are explored for digital deliberative democracy, self-governance, legislative transparency, true-cost accounting, and the ethical use of open sources and methods. Collective Intelligence is the first of a series of six books, which will also include volumes on Peace Intelligence, Commercial Intelligence, Gift Intelligence, Cultural Intelligence, and Global Intelligence.Table of Contents
Dedication i
Publisher’s Preface iii
Foreword by Yochai Benkler Remix Hassan Masum xi
The Wealth of Networks: Highlights remixed
Editor’s Preface xxi
Table of Contents xxv
A What is collective intelligence and what will we do 1
about it? (Thomas W. Malone, MIT Center for
Collective Intelligence)
B Co-Intelligence, collective intelligence, and conscious 5
evolution (Tom Atlee, Co-Intelligence Institute)
C A metalanguage for computer augmented collective 15
intelligence (Prof. Pierre Lévy, Canada Research
Chair in Collective Intelligence, FRSC)
I INDIVIDUALS & GROUPS I-01 Foresight I-01-01 Safety Glass (Karl Schroeder, science fiction author 23
and foresight consultant)
I-01-02 2007 State of the Future (Jerome C. Glenn & 29
Theodore J. Gordon, United Nations Millennium
Project)
I-02 Dialogue & Deliberation I-02-01 Thinking together without ego: Collective intelligence 39
as an evolutionary catalyst (Craig Hamilton and Claire
Zammit, Collective-Intelligence.US)
I-02-02 The World Café: Awakening collective intelligence 47
and committed action (Juanita Brown, David Isaacs
and the World Café Community)
I-02-03 Collective intelligence and the emergence of 55
wholeness (Peggy Holman, Nexus for Change, The
Change Handbook)
I-02-04 Knowledge creation in collective intelligence (Bruce 65
LaDuke, Fortune 500, HyperAdvance.com)
I-02-05 The Circle Organization: Structuring for collective 75
wisdom (Jim Rough, Dynamic Facilitation & The
Center for Wise Democracy)
I-03 Civic Intelligence I-03-01 Civic intelligence and the public sphere (Douglas 83
Schuler, Evergreen State College, Public Sphere
Project)
I-03-02 Civic intelligence and the security of the homeland 95
(John Kesler with Carole and David Schwinn,
IngeniusOnline)
I-03-03 Creating a Smart Nation (Robert Steele, OSS.Net) 107
I-03-04 University 2.0: Informing our collective intelligence 131
(Nancy Glock-Grueneich, HIGHEREdge.org)
I-03-05 Producing communities of communications and 145
foreknowledge (Jason “JZ” Liszkiewicz,
Reconfigure.org)
I-03-06 Global Vitality Report 2025: Learning to transform I-04 Electronic Communities & Distributed Cognition I-04-01 Attentional capital and the ecology of online social 163
conflict and think together effectively (Peter+Trudy networks (Derek Lomas, Social Movement Lab,
Johnson-Lenz, Johnson-Lenz.com ) UCSD)
I-04-02 A slice of life in my virtual community (Howard 173
Rheingold, Whole Earth Review, Author & Educator)
I-04-03 Shared imagination (Dr. Douglas C. Engelbart, 197
Bootstrap)
I-05 Privacy & Openness I-05-01 We’re all swimming in media: End-users must be able 201
to keep secrets (Mitch Ratcliffe, BuzzLogic &
Tetriad)
I-05-02 Working openly (Lion Kimbro, Programmer and 205
Activist)
I-06 Integral Approaches & Global Contexts I-06-01 Meta-intelligence for analyses, decisions, policy, and 213
action: The Integral Process for working on complex
issues (Sara Nora Ross, Ph.D. ARINA & Integral
Review)
I-06-02 Collective intelligence: From pyramidal to global 225
(Jean-Francois Noubel, The Transitioner)
I-06-03 Cultivating collective intelligence: A core leadership 235
competence in a complex world (George Pór, Fellow
at Universiteit van Amsterdam)
II LARGE-SCALE COLLABORATION II-01 Altruism, Group IQ, and Adaptation II-01-01 Empowering individuals towards collective online 245
production (Keith Hopper, KeithHopper.com)
II-01-02 Who’s smarter: chimps, baboons or bacteria? The 251
power of Group IQ (Howard Bloom, author)
II-01-03 A collectively generated model of the world (Marko 261
A. Rodriguez, Los Alamos National Laboratory)
II-02 Crowd Wisdom and Cognitive Bias II-02-01 Science of CI: Resources for change (Norman L 265
Johnson, Chief Scientist at Referentia Systems, former
LANL)
II-02-02 Collectively intelligent systems (Jennifer H. Watkins, 275
Los Alamos National Laboratory)
II-02-03 A contrarian view (Jaron Lanier, scholar-in-residence, 279
CET, UC Berkeley & Discover Magazine)
II-03 Semantic Structures & The Semantic Web II-03-01 Information Economy Meta Language (Interview with 283
Professor Pierre Lévy, by George Pór)
II-03-02 Harnessing the collective intelligence of the World- 293
Wide Web (Nova Spivack, RadarNetworks, Web 3.0)
II-03-03 The emergence of a global brain (Francis Heylighen, 305
Free University of Brussels)
II-04 Information Networks II-04-01 Networking and mobilizing collective intelligence (G.
Parker Rossman, Future of Learning Pioneer)
II-04-02 Toward high-performance organizations: A strategic 333
role for Groupware (Douglas C. Engelbart, Bootstrap)
II-04-03 Search panacea or ploy: Can collective intelligence 375
improve findability? (Stephen E. Arnold, Arnold IT,
Inc.)
II-05 Global Games, Local Economies, & WISER II-05-01 World Brain as EarthGame (Robert Steele and many 389
others, Earth Intelligence Network)
II-05-02 The Interra Project (Jon Ramer and many others) 399
II-05-03 From corporate responsibility to Backstory 409
Management (Alex Steffen, Executive Editor,
Worldchanging.com)
II-05-04 World Index of Environmental & Social 413
Responsibility (WISER)
By the Natural Capital Institute
II-06 Peer-Production & Open Source Hardware II-06-01 The Makers’ Bill of Rights (Jalopy, Torrone, and Hill) 421
II-06-02 3D Printing and open source design (James Duncan, 423
VP of Technology at Marketingisland)
II-06-03 REBEARTHTM: 425
II-07 Free Wireless, Open Spectrum, and Peer-to-Peer II-07-01 Montréal Community Wi-Fi (Île Sans Fil) (Interview 433
with Michael Lenczner by Mark Tovey)
II-07-02 The power of the peer-to-peer future (Jock Gill, 441
Founder, Penfield Gill Inc.)
Growing a world 6.6 billion people
would want to live in (Marc Stamos, B-Comm, LL.B)
II-07-03 Open spectrum (David Weinberger)
II-08 Mass Collaboration & Large-Scale Argumentation II-08-01 Mass collaboration, open source, and social 455
entrepreneurship (Mark Tovey, Advanced Cognitive
Engineering Lab, Institute of Cognitive Science,
Carleton University)
II-08-02 Interview with Thomas Homer-Dixon (Hassan 467
Masum, McLaughlin-Rotman Center for Global
Health)
II-08-03 Achieving collective intelligence via large-scale
argumentation (Mark Klein, MIT Center for
Collective Intelligence)
II-08-04 Scaling up open problem solving (Hassan Masum & 485
Mark Tovey)
D Afterword: The Internet and the revitalization of 495
democracy (The Rt. Honourable Paul Martin &
Thomas Homer-Dixon)
E Epilogue by Tom Atlee 513
F Three Lists 515
1. Strategic Reading Categories
2. Synopsis of the New Progressives
3. Fifty-Two Questions that Matter
G Glossary 519
H Index 52
- …