Search Results for author:
Found 18 papers, 1 papers with code
An Extension-based Approach for Computing and Verifying Preferences in Abstract Argumentation
Our research considers the inverse of the standard reasoning problem, i. e., given an abstract argumentation framework and a set of justified arguments, we compute what the possible preferences over arguments are.
Abstract Weighted Based Gradual Semantics in Argumentation Theory
While different gradual semantics have been proposed in the literature, in this paper, we identify a large family of weighted gradual semantics, called abstract weighted based gradual semantics.
Evaluation of Human-Understandability of Global Model Explanations using Decision Tree
A task based evaluation of mental models of these participants provide valuable feedback to enhance narrative global explanations.
Inferring Attack Relations for Gradual Semantics
The main contribution of our work is to demonstrate that the associated decision problem, i. e., whether a set of attacks can exist which allows the final acceptability degrees to occur for given initial weights, is NP-complete for the weighted h-categoriser and cardinality-based semantics, and is polynomial for the weighted max-based semantics, even for the complete version of the problem (where all initial weights and final acceptability degrees are known).
Utility Functions for Human/Robot Interaction
In this paper, we place ourselves in the context of human robot interaction and address the problem of cognitive robot modelling.
Analytical Solutions for the Inverse Problem within Gradual Semantics
Gradual semantics within abstract argumentation associate a numeric score with every argument in a system, which represents the level of acceptability of this argument, and from which a preference ordering over arguments can be derived.
The Inverse Problem for Argumentation Gradual Semantics
A sub-class of such semantics, the so-called weighted semantics, takes, in addition to the graph structure, an initial set of weights over the arguments as input, with these weights affecting the resultant argument ranking.
Norm Identification through Plan Recognition
Societal rules, as exemplified by norms, aim to provide a degree of behavioural stability to multi-agent societies.
Representing Pure Nash Equilibria in Argumentation
In this paper we describe an argumentation-based representation of normal form games, and demonstrate how argumentation can be used to compute pure strategy Nash equilibria.
Preference Elicitation in Assumption-Based Argumentation
Various structured argumentation frameworks utilize preferences as part of their standard inference procedure to enable reasoning with preferences.
Landmark-Based Approaches for Goal Recognition as Planning
The task of recognizing goals and plans from missing and full observations can be done efficiently by using automated planning techniques.
Using Sub-Optimal Plan Detection to Identify Commitment Abandonment in Discrete Environments
Assessing whether an agent has abandoned a goal or is actively pursuing it is important when multiple agents are trying to achieve joint goals, or when agents commit to achieving goals for each other.
Delegating via Quitting Games
Delegation allows an agent to request that another agent completes a task.
Prioritized Norms in Formal Argumentation
To resolve conflicts among norms, various nonmonotonic formalisms can be used to perform prioritized normative reasoning.
On the links between argumentation-based reasoning and nonmonotonic reasoning
In this paper we investigate the links between instantiated argumentation systems and the axioms for non-monotonic reasoning described in [9] with the aim of characterising the nature of argument based reasoning.
Subjective Logic Operators in Trust Assessment: an Empirical Study
Computational trust mechanisms aim to produce trust ratings from both direct and indirect information about agents' behaviour.
Reasoning about the Impacts of Information Sharing
In this paper we describe a decision process framework allowing an agent to decide what information it should reveal to its neighbours within a communication graph in order to maximise its utility.
