Delegated updates in epistemic graphs for opponent modelling

In an epistemic graph, belief in arguments is represented by probability distributions. Furthermore, the influence that belief in arguments can have on the belief in other arguments is represented by constraints on the probability distributions. Different agents may choose different constraints to describe their reasoning, thus making epistemic graphs extremely flexible tools. A key application for epistemic graphs is modelling participants in persuasion dialogues, with the aim of modelling the change in beliefs as each move in the dialogue is made. This requires mechanisms for updating the model throughout the dialogue. In this paper, we introduce the class of delegated update methods, which harness existing, simpler update methods in order to produce more realistic outputs. In particular, we focus on hypothesized updates, which capture agent's reluctance or susceptibility to belief updates that can be caused by certain factors, such as time of the day, fatigue, dialogue length, and more. We provide a comprehensive range of options for modelling different kinds of agents and we explore a range of properties for categorising the options

Strategic Argumentation Dialogues for Persuasion: Framework and Experiments Based on Modelling the Beliefs and Concerns of the Persuadee

Persuasion is an important and yet complex aspect of human intelligence. When undertaken through dialogue, the deployment of good arguments, and therefore counterarguments, clearly has a significant effect on the ability to be successful in persuasion. Two key dimensions for determining whether an argument is good in a particular dialogue are the degree to which the intended audience believes the argument and counterarguments, and the impact that the argument has on the concerns of the intended audience. In this paper, we present a framework for modelling persuadees in terms of their beliefs and concerns, and for harnessing these models in optimizing the choice of move in persuasion dialogues. Our approach is based on the Monte Carlo Tree Search which allows optimization in real-time. We provide empirical results of a study with human participants showing that our automated persuasion system based on this technology is superior to a baseline system that does not take the beliefs and concerns into account in its strategy.Comment: The Data Appendix containing the arguments, argument graphs, assignment of concerns to arguments, preferences over concerns, and assignment of beliefs to arguments, is available at the link http://www0.cs.ucl.ac.uk/staff/a.hunter/papers/unistudydata.zip The code is available at https://github.com/ComputationalPersuasion/MCC

Strategic argumentation dialogues for persuasion: Framework and experiments based on modelling the beliefs and concerns of the persuadee

Persuasion is an important and yet complex aspect of human intelligence. When undertaken through dialogue, the deployment of good arguments, and therefore counterarguments, clearly has a significant effect on the ability to be successful in persuasion. Two key dimensions for determining whether an argument is 'good' in a particular dialogue are the degree to which the intended audience believes the argument and counterarguments, and the impact that the argument has on the concerns of the intended audience. In this paper, we present a framework for modelling persuadees in terms of their beliefs and concerns, and for harnessing these models in optimizing the choice of move in persuasion dialogues. Our approach is based on the Monte Carlo Tree Search which allows optimization in real-time. We provide empirical results of a study with human participants that compares an automated persuasion system based on this technology with a baseline system that does not take the beliefs and concerns into account in its strategy

The Emergent Politics of Geoengineering

This thesis examines the role of science in the earliest stages of the political process. It does this by studying the emergence of ‘geoengineering’ on the political agenda. The term describes a set of ideas on how to stabilize global temperature by intervening into the Earth’s natural systems, and was subject to a strong taboo in the scientific community until the mid-2000s. Yet within a decade, it has become relevant to international climate politics. To understand how this transition took place, the thesis uses mixed methods to study the causal mechanisms by which geoengineering became an object of governance. Paper I describes the internal dynamics of a scientific community that helped transform geoengineering into a distinct, salient and malleable governance object. It explains how social cohesion, brokerage and diversity acted as important mechanisms in this process. Paper II studies the role of authoritative scientific assessments in making geoengineering a normal and relevant topic for research. It shows how such assessments act as a form of de facto governance in shaping the activities of a research landscape. Paper III identifies similarities and differences in the way that different sub-areas of climate change policy are governed. It suggests that, if a problem structure is perceived to be malign, this makes it less conducive to public governance. Conversely, if a problem structure comes to be perceived as more benign, this facilitates public governance. Paper IV examines the role of problem definition and ‘institutional fit’, evaluating how geoengineering matches with the expectations of government actors. It discusses three areas where such fit is lacking, and how this makes it difficult for government officials to form a political position on geoengineering. The results of this study flow into the description of a pattern that seems to be important at many different stages of the opinion-shaping process. This pattern includes the introduction of a topic to a new audience; the audience’s heated debate around this topic; the intervention of an actor with authority; and the streamlining of the audience’s debate according to the authoritative actor’s judgement. Found at many different levels of the political process, the pattern may explain why some topics become subject to political decision making, and others do not

Abstraction in Model Checking Multi-Agent Systems

This thesis presents existential abstraction techniques for multi-agent systems preserving temporal-epistemic specifications. Multi-agent systems, defined in the interpreted system frameworks, are abstracted by collapsing the local states and actions of each agent. The goal of abstraction is to reduce the state space of the system under investigation in order to cope with the state explosion problem that impedes the verification of very large state space systems. Theoretical results show that the resulting abstract system simulates the concrete one. Preservation and correctness theorems are proved in this thesis. These theorems assure that if a temporal-epistemic formula holds on the abstract system, then the formula also holds on the concrete one. These results permit to verify temporal-epistemic formulas in abstract systems instead of the concrete ones, therefore saving time and space in the verification process. In order to test the applicability, usefulness, suitability, power and effectiveness of the abstraction method presented, two different implementations are presented: a tool for data-abstraction and one for variable-abstraction. The first technique achieves a state space reduction by collapsing the values of the domains of the system variables. The second technique performs a reduction on the size of the model by collapsing groups of two or more variables. Therefore, the abstract system has a reduced number of variables. Each new variable in the abstract system takes values belonging to a new domain built automatically by the tool. Both implementations perform abstraction in a fully automatic way. They operate on multi agents models specified in a formal language, called ISPL (Interpreted System Programming Language). This is the input language for MCMAS, a model checker for multi-agent systems. The output is an ISPL file as well (with a reduced state space). This thesis also presents several suitable temporal-epistemic examples to evaluate both techniques. The experiments show good results and point to the attractiveness of the temporal-epistemic abstraction techniques developed in this thesis. In particular, the contributions of the thesis are the following ones: • We produced correctness and preservation theoretical results for existential abstraction. • We introduced two algorithms to perform data-abstraction and variable-abstraction on multi-agent systems. • We developed two software toolkits for automatic abstraction on multi-agent scenarios: one tool performing data-abstraction and the second performing variable-abstraction. • We evaluated the methodologies introduced in this thesis by running experiments on several multi-agent system examples

Proceedings of The Multi-Agent Logics, Languages, and Organisations Federated Workshops (MALLOW 2010)

http://ceur-ws.org/Vol-627/allproceedings.pdfInternational audienceMALLOW-2010 is a third edition of a series initiated in 2007 in Durham, and pursued in 2009 in Turin. The objective, as initially stated, is to "provide a venue where: the cost of participation was minimum; participants were able to attend various workshops, so fostering collaboration and cross-fertilization; there was a friendly atmosphere and plenty of time for networking, by maximizing the time participants spent together"

Systems action design research : delineation of an application to develop hybrid local climate services

In this thesis, a Systems Action Design Research (SADR) model was developed, which allows the Action Design Research Paradigm to be extended to process hybrid systems of stationary or changing interacting systems; including both quantitative and qualitative aspects. The crucial challenge is to get the experts and grass-root end-users to work together actively in a participatory and cocreative way instead of the foremost current expert dominated practices. Hence the basic model is engaged with an epistemic Delphi entry process, which considers the particular application. This study delineates a unique application to develop hybrid local climate services, which take into account also humanitarian values and presents three case studies done in Mozambique, Kenya, and Tanzania conducted by design thinking.Tutkimuksessa on kehitetty vuorovaikutteisten järjestelmien toiminnan suunnittelun tutkimusmalli, joka laajentaa aikaisempia toiminnan suunnittelun tutkimusmalleja stationaarisiin tai muuttuviin vuorovaikutteisiin mahdollisimman kokonaisvaltaisiin eli hybrideihin järjestelmiin. Malli ottaa huomioon sekä määrällisiä että laadullisia tekijöitä. Vielä nykyisin vallalla olevien asiantuntijapainotteisten käytäntöjen välttämättömänä haasteena on saattaa asiantuntijat ja ruohonjuuritason loppukäyttäjät työskentelemään yhteisen luovuuden merkeissä osallistavalla tavalla. Tästä syystä kehitetyn mallin olennaisena osana on episteeminen, sovelluskohtainen Delphi-prosessi. Sovelluksena toteutettavien hybridien paikallisten loppukäyttäjien tietotarpeita palvelevien mobiili-ilmastomallien osalta viitoitetaan tämän sovelluksen pääpiirteet tutkimuksessa esitetyn mallin näkökulmasta sekä esitetään kolmen Itä-Afrikassa (Mosambik, Kenia ja Tansania) suunnitteluajattelun mukaisesti toteutetun ideointiprojektin ehdotukset. Kehitettävissä mobiiliilmastopalveluissa otetaan soveltuvin osin huomioon myös humanitaariset arvot. Tulokset osoittavat, että kehitetty malli voi avata uusia näköaloja hybridien paikallisten mobiili-ilmastopalvelujen kehittämiseen ruohonjuuritason viljelijöille

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

Probabilistic Logics in Foresight

A prudent decision-maker facing a complicated strategic decision considers the factors relevant to the decision, gathers information about the identified factors, and attempts to formulate the best course of action based on the available information. Careful consideration of any alternative course of action might reveal that in addition to the desirable intended consequences, a number of less desirable outcomes are likely to follow as well. Facing a complicatedly entangled net of considerations, entwined positive and negative outcomes, and uncertainty, the decision-maker will attempt to organize the available information and make the decision by using some strategy of reasoning on the information. A logic is away of reasoning adherent to rules, based on structured knowledge. A modeling language and inference rules comprise a logic. The language of a logic is formal, consisting of a defined set of building blocks having well defined meanings. The decision-maker can use a modeling language to describe the information pertinent to the decision-making problem, and organize the information by giving it a structure, which specifies the relationships between the individual considerations. While reasoning about the extensive amount of information in its disorganized form may be overwhelming, in a structured form the information becomes much more useful for the decision-maker, as nowit can be analyzed in a systematic fashion. Inference is systematic reasoning about structured information. As the information is described in a formal and structured way and the process of reasoning about it is systematic, the inference may be automated. Computational inference permits reasoning that would not be possible by intuition in cases where the amount of considerations and their interdependencies exceeds human cognitive capacity. The decision-maker may direct the efforts to describing the decision factors and knowledge with the formal language, with a narrower and more manageable frame of attention, and perform the inference with a computer. Probabilistic language gives room for haziness in knowledge description, and is thus suitable for describing knowledge originating from humans, conveyed to the decision-maker in a non-formal format, such as viewpoints and opinions. Many domains of decision-making and planning use human sourced knowledge, especially if the informants are knowledgeable people or experts with relevant, developed understanding on the domain issues. The expert views can augment the knowledge bases in cases where other forms of information, such as empirical or statistical data, are lacking or completely absent, or do not capture or represent considerations important for the decision-making. This is a typical setting for strategic decision-making, long range planning, and foresight, which have to account for developments and phenomena that do not yet exist in the form they might in the future, or at all. This work discusses approaches for decision support and foresight oriented modeling of expert knowledge bases and inference based on such knowledge bases. Two novel approaches developed by the author are presented and positioned against previous work on cross-impact analysis, structural and morphological analysis, and Bayesian networks. The proposed approaches are called EXIT and AXIOM. EXIT is a conceptually simple approach for structural analysis, based on a previously unutilized computational process for discovery of higher-order influences in a structural model. The analytical output is, in relation to comparable approaches, easier to interpret considering the causal information content of the structural model. AXIOM is a versatile probabilistic logic, combining ideas of structural analysis, morphological analysis, cross-impact analysis and Bayesian belief networks. It provides outputs comparable to Bayesian networks, but has higher fitness for full model parameterization through expert elicitation. A guiding idea of the methodological development work has been that the slightly aged toolset of cross-impact analysis can be updated, improved and extended, and brought to be more interoperable with the Bayesian approach

Private and censorship-resistant communication over public networks

Society’s increasing reliance on digital communication networks is creating unprecedented opportunities for wholesale surveillance and censorship. This thesis investigates the use of public networks such as the Internet to build robust, private communication systems that can resist monitoring and attacks by powerful adversaries such as national governments. We sketch the design of a censorship-resistant communication system based on peer-to-peer Internet overlays in which the participants only communicate directly with people they know and trust. This ‘friend-to-friend’ approach protects the participants’ privacy, but it also presents two significant challenges. The first is that, as with any peer-to-peer overlay, the users of the system must collectively provide the resources necessary for its operation; some users might prefer to use the system without contributing resources equal to those they consume, and if many users do so, the system may not be able to survive. To address this challenge we present a new game theoretic model of the problem of encouraging cooperation between selfish actors under conditions of scarcity, and develop a strategy for the game that provides rational incentives for cooperation under a wide range of conditions. The second challenge is that the structure of a friend-to-friend overlay may reveal the users’ social relationships to an adversary monitoring the underlying network. To conceal their sensitive relationships from the adversary, the users must be able to communicate indirectly across the overlay in a way that resists monitoring and attacks by other participants. We address this second challenge by developing two new routing protocols that robustly deliver messages across networks with unknown topologies, without revealing the identities of the communication endpoints to intermediate nodes or vice versa. The protocols make use of a novel unforgeable acknowledgement mechanism that proves that a message has been delivered without identifying the source or destination of the message or the path by which it was delivered. One of the routing protocols is shown to be robust to attacks by malicious participants, while the other provides rational incentives for selfish participants to cooperate in forwarding messages