25,969 research outputs found
Human-Agent Decision-making: Combining Theory and Practice
Extensive work has been conducted both in game theory and logic to model
strategic interaction. An important question is whether we can use these
theories to design agents for interacting with people? On the one hand, they
provide a formal design specification for agent strategies. On the other hand,
people do not necessarily adhere to playing in accordance with these
strategies, and their behavior is affected by a multitude of social and
psychological factors. In this paper we will consider the question of whether
strategies implied by theories of strategic behavior can be used by automated
agents that interact proficiently with people. We will focus on automated
agents that we built that need to interact with people in two negotiation
settings: bargaining and deliberation. For bargaining we will study game-theory
based equilibrium agents and for argumentation we will discuss logic-based
argumentation theory. We will also consider security games and persuasion games
and will discuss the benefits of using equilibrium based agents.Comment: In Proceedings TARK 2015, arXiv:1606.0729
Impact of Argument Type and Concerns in Argumentation with a Chatbot
Conversational agents, also known as chatbots, are versatile tools that have
the potential of being used in dialogical argumentation. They could possibly be
deployed in tasks such as persuasion for behaviour change (e.g. persuading
people to eat more fruit, to take regular exercise, etc.) However, to achieve
this, there is a need to develop methods for acquiring appropriate arguments
and counterargument that reflect both sides of the discussion. For instance, to
persuade someone to do regular exercise, the chatbot needs to know
counterarguments that the user might have for not doing exercise. To address
this need, we present methods for acquiring arguments and counterarguments, and
importantly, meta-level information that can be useful for deciding when
arguments can be used during an argumentation dialogue. We evaluate these
methods in studies with participants and show how harnessing these methods in a
chatbot can make it more persuasive
Proceedings ICPW'07: 2nd International Conference on the Pragmatic Web, 22-23 Oct. 2007, Tilburg: NL
Proceedings ICPW'07: 2nd International Conference on the Pragmatic Web, 22-23 Oct. 2007, Tilburg: N
A Labelling Framework for Probabilistic Argumentation
The combination of argumentation and probability paves the way to new
accounts of qualitative and quantitative uncertainty, thereby offering new
theoretical and applicative opportunities. Due to a variety of interests,
probabilistic argumentation is approached in the literature with different
frameworks, pertaining to structured and abstract argumentation, and with
respect to diverse types of uncertainty, in particular the uncertainty on the
credibility of the premises, the uncertainty about which arguments to consider,
and the uncertainty on the acceptance status of arguments or statements.
Towards a general framework for probabilistic argumentation, we investigate a
labelling-oriented framework encompassing a basic setting for rule-based
argumentation and its (semi-) abstract account, along with diverse types of
uncertainty. Our framework provides a systematic treatment of various kinds of
uncertainty and of their relationships and allows us to back or question
assertions from the literature
Development of multiple media documents
Development of documents in multiple media involves activities in three different
fields, the technical, the discoursive and the procedural. The major development problems of
artifact complexity, cognitive processes, design basis and working context are located where these
fields overlap. Pending the emergence of a unified approach to design, any method must allow for
development at the three levels of discourse structure, media disposition and composition, and
presentation. Related work concerned with generalised discourse structures, structured
documents, production methods for existing multiple media artifacts, and hypertext design offer
some partial forms of assistance at different levels. Desirable characteristics of a multimedia
design method will include three phases of production, a variety of possible actions with media
elements, an underlying discoursive structure, and explicit comparates for review
Collective intelligence for OER sustainability
To thrive, the Open Educational Resource (OER) movement, or a given initiative, must make sense of a complex, changing environment. Since “sustainability” is a desirable systemic capacity that our community should display, we consider a number of principles that sharpen the concept: resilience, sensemaking and complexity. We outline how these motivate the concept of collective intelligence (CI), we give examples of what OER-CI might look like, and we describe the emerging Cohere CI platform we are developing in response to these requirements
Complexity, strategic thinking and organisational change
Comparative considerations of strategy from complexity paradigm and Newtonian paradigm perspectives are discussed in the light of three ideological dispositions towards the future. We term them defensive, opportunist, and goal oriented. Over the years, the strategy literature has identified a number of strategic archetypes (e.g. Miller and Freisen, 1978). What is interesting from our point of view is the patterns of reasoning that underpin them. The study of ideology has identified qualitative patterns of reasoning which underpin different types of strategic decision in both the fields of politics and strategic management. This paper considers three patterns of reasoning and considers how they relate to the complexity and Newtonian paradigms
Acquiring knowledge from expert agents in a structured argumentation setting
Information-seeking interactions in multi-agent systems are required for situations in which there exists an expert agent that has vast knowledge about some topic, and there are other agents (questioners or clients) that lack and need information regarding that topic. In this work, we propose a strategy for automatic knowledge acquisition in an information-seeking setting in which agents use a structured argumentation formalism for knowledge representation and reasoning. In our approach, the client conceives the other agent as an expert in a particular domain and is committed to believe in the expert's qualified opinion about a given query. The client's goal is to ask questions and acquire knowledge until it is able to conclude the same as the expert about the initial query. On the other hand, the expert's goal is to provide just the necessary information to help the client understand its opinion. Since the client could have previous knowledge in conflict with the information acquired from the expert agent, and given that its goal is to accept the expert's position, the client may need to adapt its previous knowledge. The operational semantics for the client-expert interaction will be defined in terms of a transition system. This semantics will be used to formally prove that, once the client-expert interaction finishes, the client will have the same assessment the expert has about the performed query.Fil: Agis, Ramiro Andrés. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; ArgentinaFil: Gottifredi, Sebastián. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; ArgentinaFil: García, Alejandro Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; Argentin
Towards a framework for computational persuasion with applications in behaviour change
Persuasion is an activity that involves one party trying to induce another party to believe something or to do something. It is an important and multifaceted human facility. Obviously, sales and marketing is heavily dependent on persuasion. But many other activities involve persuasion such as a doctor persuading a patient to drink less alcohol, a road safety expert persuading drivers to not text while driving, or an online safety expert persuading users of social media sites to not reveal too much personal information online. As computing becomes involved in every sphere of life, so too is persuasion a target for applying computer-based solutions. An automated persuasion system (APS) is a system that can engage in a dialogue with a user (the persuadee) in order to persuade the persuadee to do (or not do) some action or to believe (or not believe) something. To do this, an APS aims to use convincing arguments in order to persuade the persuadee. Computational persuasion is the study of formal models of dialogues involving arguments and counterarguments, of user models, and strategies, for APSs. A promising application area for computational persuasion is in behaviour change. Within healthcare organizations, government agencies, and non-governmental agencies, there is much interest in changing behaviour of particular groups of people away from actions that are harmful to themselves and/or to others around them
- …