Abstract
In dialogical argumentation, a participant is often unsure what moves the other participant(s) might make. If the dialogue is proceeding according to some accepted protocol, then a participant might be able to determine what are the possible moves that the other might make, but the participant might be unsure as to which move will be chosen by the other agent. In this paper, propositional executable logic is augmented with probabilities that reflect the probability that any given move will be chosen by the agent. This provides a simple and lucid language that can be executed to generate a dialogue. Furthermore, a set of such rules for each agent can be represented by a probabilistic finite state machine (PFSM). For modelling dialogical argumentation, a PFSM can be used by one agent to model how the other agent may react to any dialogical move. An agent can then analyze the PFSM to determine the most likely outcomes of a dialogue given any choices it makes. This can be used by the agent to determine its choice of moves in order to optimize its outcomes from the dialogue.
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Hunter, A. (2014). Probabilistic Strategies in Dialogical Argumentation. In: Straccia, U., Calì, A. (eds) Scalable Uncertainty Management. SUM 2014. Lecture Notes in Computer Science(), vol 8720. Springer, Cham. https://doi.org/10.1007/978-3-319-11508-5_16
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DOI: https://doi.org/10.1007/978-3-319-11508-5_16
Publisher Name: Springer, Cham
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