Abstract
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.
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Notes
- 1.
We based our empathic agent on a rationality-oriented definition of empathy, to avoid the technical ambiguity definitions that focus on emotional empathy imply. A comprehensive discussion of definitions of empathy is beyond the scope of this work.
- 2.
Note that \(\mathop {\text {arg max}}u_{A_i}\) returns a set of sets.
- 3.
Note that a single acceptability rule does not necessarily consider all to-be-executed actions, i.e. it might ignore some of its input arguments.
- 4.
As the simple examples we implement in this paper feature only one acting agent (a second agent is merely approving or disapproving of the actions), such game-theoretical considerations are beyond scope. Hence, we will not elaborate further on them.
- 5.
For now, we assume all agents in a given scenario have the same implementation variant. Empathic agents that are capable to effectively interact with empathic agents of other implementation variants or with non-empathic agents are–although interesting–beyond scope.
- 6.
The implementation of our empathic agents with Jason (including the Jason extension we introduce below, as well as a technical report that documents the implementation) is available at https://github.com/TimKam/empathic-jason.
- 7.
The mappings are end-user specific. In a scenario with multiple end-users, the persuader would have one set of mappings per user.
- 8.
Note that in Jason terminology, acceptability rules are beliefs and not rules.
- 9.
If at any step of the decision process, several actions could be picked because they provide the same utility, the agents will always pick the first one in the corresponding list to reach a deterministic result.
- 10.
Note that we compare different argumentation semantics in Sect. 5.
- 11.
However, the provided example code implements only one argumentation cycle.
- 12.
In Example 2, we illustrate an empathic agent argumentation scenario, in which grounded semantics are overly strict.
- 13.
For the sake of simplicity, we use a wild card (\(*\)) to denote that the acceptability rule applies no matter which preference the mitigator agent has. Note that this syntax is not supported by our implementation.
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Acknowledgements
We thank the anonymous reviewers for their constructive feedback. This work was partially supported by the Wallenberg AI, Autonomous Systems and Software Program (WASP) funded by the Knut and Alice Wallenberg Foundation.
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Kampik, T., Nieves, J.C., Lindgren, H. (2019). Implementing Argumentation-Enabled Empathic Agents. In: Slavkovik, M. (eds) Multi-Agent Systems. EUMAS 2018. Lecture Notes in Computer Science(), vol 11450. Springer, Cham. https://doi.org/10.1007/978-3-030-14174-5_10
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