Université de Fribourg

Solving the apparent diversity-accuracy dilemma of recommender systems

Zhou, Tao ; Kuscsik, Zoltán ; Liu, Jian-Guo ; Medo, Matúš ; Wakeling, Joseph Rushton ; Zhang, Yi-Cheng

In: Proceedings of the National Academy of Sciences of the USA - PNAS, 2010, vol. 107, no. 10, p. 4511-4515

Recommender systems use data on past user preferences to predict possible future likes and interests. A key challenge is that while the most useful individual recommendations are to be found among diverse niche objects, the most reliably accurate results are obtained by methods that recommend objects based on user or object similarity. In this paper we introduce a new algorithm specifically to...

Université de Fribourg

Reducing the heterogeneity of payoffs: an effective way to promote cooperation in the prisoner's dilemma game

Jiang, Luo-Luo ; Zhao, Ming ; Yang, Han-Xin ; Wakeling, Joseph Rushton ; Wang, Bing-Hong ; Zhou, Tao

In: Physical Review E, 2009, vol. 80, p. 031144

In this paper, the accumulated payoff of each agent is regulated so as to reduce the heterogeneity of the distribution of all such payoffs. It is found that there exists an optimal regulation strength at which cooperation in the prisoner's dilemma game is optimally promoted. If the heterogeneity is regulated to be either too weak or too strong, the promotive effect disappears and the evolution of...

Université de Fribourg

Adaptivity and ‘Per learning’

Wakeling, Joseph Rushton

One of the key points addressed by Per Bak in his models of brain function was that biological neural systems must be able not just to learn, but also to adapt—to quickly change their behaviour in response to a changing environment. I discuss this in the context of various simple learning rules and adaptive problems, centred around the Chialvo-Bak ‘minibrain’ model (Neurosci. 90 (1999)...