Normative Practical Reasoning via Argumentation and Dialogue
Authors: Zohreh Shams, Marina De Vos, Nir Oren, Julian Padget
IJCAI 2016 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | In this paper we propose an argumentation-based approach to normative practical reasoning using a dialogue game to provide an intuitive overview of agent s reasoning. In achieving this aim, the following contributions are made: (i) we formalise a set of argument schemes and critical questions [Walton, 1996] aimed at checking plan justifiability with respect to goal satisfaction and norm compliance/violation; (ii) we offer a novel decision criterion that identifies the best plan(s) both in the presence and absence of preferences over goals and norms; and (iii) we investigate the properties of the best plan(s). These properties, together with Caminada s Socratic dialogu game [Caminada et al., 2014a], are used to generate an explanation for the justifiability of the best plan(s). ... In future work we will investigate temporal solutions to addressing goal-goal and goal-norm conflict, similar to how conflicts between norms are handled. We also intend to empirically evaluate the effectiveness of our explanations, determining how likely a human is to accept the recommendation of a system regarding the best plan(s). |
| Researcher Affiliation | Academia | a Department of Computer Science, University of Bath, UK {z.shams, m.d.vos, j.a.padget}@bath.ac.uk b Department of Computing Science, University of Aberdeen, UK n.oren@abdn.ac.uk |
| Pseudocode | No | The paper provides definitions and describes a theoretical framework with properties and examples, but it does not include any pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not mention providing open-source code for the described methodology. There are no links or statements about code availability. |
| Open Datasets | No | The paper is theoretical and uses worked examples (e.g., Example 6) rather than empirical datasets for training or evaluation. Therefore, there is no mention of publicly available datasets for training. |
| Dataset Splits | No | The paper is theoretical and does not describe empirical experiments involving data splits for training, validation, or testing. |
| Hardware Specification | No | The paper is theoretical and does not describe empirical experiments, thus no hardware specifications are mentioned. |
| Software Dependencies | No | The paper is theoretical and does not describe empirical experiments, therefore no specific software dependencies with version numbers are mentioned. |
| Experiment Setup | No | The paper is theoretical and does not describe empirical experiments, thus no experimental setup details like hyperparameters or system-level training settings are provided. |