Abstract
Reputation is generally defined as the opinion of a group on an aspect of a thing. This paper presents a reputation model that follows a probabilistic modeling of opinions based on three main concepts: (1) the value of an opinion decays with time, (2) the reputation of the opinion source impacts the reliability of the opinion, and (3) the certainty of the opinion impacts its weight with respect to other opinions. Furthermore, the model is flexible with its opinion sources: it may use explicit opinions or implicit opinions that can be extracted from agent behaviour in domains where explicit opinions are sparse. We illustrate the latter with an approach to extract opinions from behavioral information in the sports domain, focusing on football in particular. One of the uses of a reputation model is predicting behaviour. We take up the challenge of predicting the behavior of football teams in football matches, which we argue is a very interesting yet difficult approach for evaluating the model.
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Notes
- 1.
We note that we look for values that are approximately greater (\(\gtrapprox \)), approximately less than (\(\lessapprox \)), or approximately equal (\(\approx \)) to \(\frac{1}{2}\). In practice, this is achieved by defining three different intervals to describe this.
- 2.
Data were extracted from http://www.lfp.es/LigaBBVA/Liga_BBVA_Resultados.aspx.
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Acknowledgements
This work is supported by the Agreement Technologies project (CONSOLIDER CSD2007-0022, INGENIO 2010) and the PRAISE project (EU FP7 grant number 388770).
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Osman, N., Provetti, A., Riggi, V., Sierra, C. (2015). MORE: Merged Opinions Reputation Model. In: Bulling, N. (eds) Multi-Agent Systems. EUMAS 2014. Lecture Notes in Computer Science(), vol 8953. Springer, Cham. https://doi.org/10.1007/978-3-319-17130-2_5
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