Implementing Argumentation-enabled Empathic Agents

In a previous publication, we introduced the core concepts of empathic agents as agents that use a combination of utility-based and rule-based approaches to resolve conflicts when interacting with other agents in their environment. In this work, we implement proof-of-concept prototypes of empathic agents with the multi-agent systems development framework Jason and apply argumentation theory to extend the previously introduced concepts to account for inconsistencies between the beliefs of different agents. We then analyze the feasibility of different admissible set-based argumentation semantics to resolve these inconsistencies. As a result of the analysis we identify the maximal ideal extension as the most feasible argumentation semantics for the problem in focus.Comment: Accepted for/presented at the 16th European Conference on Multi-Agent Systems (EUMAS 2018

Understanding The Impact of Solver Choice in Model-Based Test Generation

Background: In model-based test generation, SMT solvers explore the state-space of the model in search of violations of specified properties. If the solver finds that a predicate can be violated, it produces a partial test specification demonstrating the violation.Aims: The choice of solvers is important, as each may produce differing counterexamples. We aim to understand how solver choice impacts the effectiveness of generated test suites at finding faults.Method: We have performed experiments examining the impact of solver choice across multiple dimensions, examining the ability to attain goal satisfaction and fault detection when satisfaction is achieved---varying the source of test goals, data types of model input, and test oracle.Results: The results of our experiment show that solvers vary in their ability to produce counterexamples, and---for models where all solvers achieve goal satisfaction---in the resulting fault detection of the generated test suites. The choice of solver has an impact on the resulting test suite, regardless of the oracle, model structure, or source of testing goals.Conclusions: The results of this study identify factors that impact fault-detection effectiveness, and advice that could improve future approaches to model-based test generation

A complete calculus for Max-SAT

Max-SAT is the problem of finding an assignment minimizing the number of unsatisfied clauses of a given CNF formula. We propose a resolution-like calculus for Max-SAT and prove its soundness and completeness. We also prove the completeness of some refinements of this calculus. From the completeness proof we derive an exact algorithm for Max-SAT and a time upper bound

Extending modular semantics for bipolar weighted argumentation (extended abstract)

Weighted bipolar argumentation frameworks allow modeling arguments and their relationships in order to decide which arguments can be accepted. Arguments have an initial weight that is adapted based on the strength of their attackers and supporters. Applications include decision support, social media analysis and information retrieva

A probabilistic author-centered model for Twitter discussions

In a recent work some of the authors have developed an argumentative approach for discovering relevant opinions in Twitter discussions with probabilistic valued relationships. Given a Twitter discussion, the system builds an argument graph where each node denotes a tweet and each edge denotes a criticism relationship between a pair of tweets of the discussion. Relationships between tweets are associated with a probability value, indicating the uncertainty that the relationships hold. In this work we introduce and investigate a natural extension of the representation model, referred as probabilistic author-centered model, in which tweets within a discussion are grouped by authors, in such a way that tweets of a same author describe his/her opinion in the discussion and are rep- resented with a single node in the graph, and criticism relationships denote controversies between opinions of Twitter users in the discussion. In this new model, the interactions between authors can give rise to circular criticism relationships, and the probability of one opinion criticizing another has to be evaluated from the probabilities of criticism among the tweets that compose both opinions.This work was partially funded by the Spanish MICINN Projects TIN2015-71799-C2-1-P and TIN2015-71799-C2-2-PPeer Reviewe

Fuzzy Argumentation System for Decision Support

International audienceWe introduce in this paper a quantitative preference based argumentation system relying on ASPIC argumentation framework and fuzzy set theory. The knowledge base is fuzzified to allow the experts to express their expertise (premises and rules) attached with grades of importance in the unit interval. Arguments are attached with a score aggregating the importance expressed on their premises and rules. Extensions are then computed and the strength of each of which can also be obtained based on its strong arguments. The strengths are used to rank fuzzy extensions from the strongest to the weakest one, upon which decisions can be made. The approach is finally used for decision making in a real world application within the EcoBioCap project