Time and defeasibility in FIPA ACL semantics

AbstractInferences about speech acts are often conditional, non-monotonic, and involve the issue of time. Most agent communication languages, however, ignore these issues, due to the difficulty to combine them in a single formalism. This paper addresses such issues in defeasible logic, and shows how to express a semantics for ACLs in order to make non-monotonic inferences on the basis of speech acts

On Learning Attacks in Probabilistic Abstract Argumentation

ABSTRACT Probabilistic argumentation combines the quantitative uncertainty accounted by probability theory with the qualitative uncertainty captured by argumentation. In this paper, we investigate the problem of learning the structure of an argumentative graph to account for (a distribution of) labellings of a set of arguments. We consider a general abstract framework, where the structure of arguments is left unspecified, and we focus on the grounded semantics. We present, with experimental insights, an anytime algorithm evaluating 'on the fly' hypothetical attacks from the examination of an input stream of labellings. Keywords Probabilistic Abstract Argumentation; Structure Learning

Probabilistic Rule-Based Argumentation for Norm-Governed Learning Agents

This paper proposes an approach to investigate norm-governed learning agents which combines a logic-based formalism with an equation-based counterpart. This dual formalism enables us to describe the reasoning of such agents and their interactions using argumentation, and, at the same time, to capture systemic features using equations. The approach is applied to norm emergence and internalisation in systems of learning agents. The logical formalism is rooted into a probabilistic defeasible logic instantiating Dung’s argumentation framework. Rules of this logic are attached with probabilities to describe the agents’ minds and behaviours as well as uncertain environments. Then, the equation-based model for reinforcement learning, defined over this probability distribution, allows agents to adapt to their environment and self-organise

Legal Consolidation formalised in Defeasible Logic and based on Agents.

Abstract. Updated legal corpora have been indicated by the European Union as fundamental to eDemocracy, and member states looking to set up eGovernment initiatives are acting on that input. However, the usual automation of legal consolidation presents shortcomings, namely, the collapse of temporal dimensions and local views of normative systems. This paper presents solutions to these shortcomings by providing the formalisation in logic of an appropriate legal temporal model and an investigation of the use of the multi-agent paradigm

Evaluation of logic-based smart contracts for blockchain systems

Date: 28 June 2016While procedural languages are commonly used to program smart contracts in blockchain systems, logic-based languages may be interesting alternatives. In this paper, we inspect what are the possible legal and technical (dis)advantages of logic-based smart contracts in light of common activities featuring ordinary contracts, then we provide insights on how to use such logic-based smart contracts in combination with blockchain systems. These insights lead us to emphasize a fundamental challenge - algorithms for logic approaches have to be efficient, but they also need to be literally cheap as measured within the environment where they are deployed and according to its economic rules. We illustrate this with different algorithms from defeasible logic-based frameworks

On the Justification of Statements in Argumentation-based Reasoning

Abstract In the study of argumentation-based reasoning, argument justification has received far more attention than statement justification, often treated as a simple byproduct of the former. As a consequence, counterintuitive results and significant losses of sensitivity can be identified in the treatment of statement justification by otherwise appealing formalisms. To overcome this limitation, we propose to reappraise statement justification as a formalism-independent component. To this purpose, we introduce a novel general model of argumentationbased reasoning based on multiple levels of labellings, one of which is devoted to statement justification. This model is able to encompass several literature proposals as special cases: we illustrate this ability for the case of the ASPIC + formalism and provide a first example of tunable statement justification in this context

Success chances in argument games : a probabilistic approach to legal disputes

The outcome of a legal dispute, namely, the decision of its adjudicator, is uncertain, and both parties develop their strategies on the basis of their appreciation of the probability that the adjudicator will accept their arguments or the arguments of their adversary. Costs and gains have to be balanced in light of this uncertainty in order to identify the most convenient strategies. This paper provides a probabilistic approach embedded into an argumentation framework to capture this uncertainty and its use to determine the expected utility to engage in a legal dispute