121 research outputs found

    Learning in Repeated Games: Human Versus Machine

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    While Artificial Intelligence has successfully outperformed humans in complex combinatorial games (such as chess and checkers), humans have retained their supremacy in social interactions that require intuition and adaptation, such as cooperation and coordination games. Despite significant advances in learning algorithms, most algorithms adapt at times scales which are not relevant for interactions with humans, and therefore the advances in AI on this front have remained of a more theoretical nature. This has also hindered the experimental evaluation of how these algorithms perform against humans, as the length of experiments needed to evaluate them is beyond what humans are reasonably expected to endure (max 100 repetitions). This scenario is rapidly changing, as recent algorithms are able to converge to their functional regimes in shorter time-scales. Additionally, this shift opens up possibilities for experimental investigation: where do humans stand compared with these new algorithms? We evaluate humans experimentally against a representative element of these fast-converging algorithms. Our results indicate that the performance of at least one of these algorithms is comparable to, and even exceeds, the performance of people

    Adaptive Network Based Fuzzy Inference System and the Future of Employability

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    Educational data is considered by researchers and data scientists as an indicator for the future predictions. The current research study aims for classifying IT alumni students into employed and unemployed. The data collected from two universities in Jordan. 781 of IT alumni students in two universities in Jordan participate in the current study. Three classifiers are compared to determine the most suitable one for predicting the future of IT students’ employability. The results show that Adaptive Network Based Fuzzy Inference System came as a suitable classifier for predicting IT students’ employment in Jordan. As gender, programming skills, and communication skills came as the most effective factors affecting IT recruitment field, a set of recommendations is presented to the ministry of higher education based on the significant factors affecting IT graduates employment. Keywords: employability, ANFIS, classification, data mining DOI: 10.7176/NCS/12-04 Publication date: January 31st 202

    Corruption Drives the Emergence of Civil Society

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    Peer punishment of free-riders (defectors) is a key mechanism for promoting cooperation in society. However, it is highly unstable since some cooperators may contribute to a common project but refuse to punish defectors. Centralized sanctioning institutions (for example, tax-funded police and criminal courts) can solve this problem by punishing both defectors and cooperators who refuse to punish. These institutions have been shown to emerge naturally through social learning and then displace all other forms of punishment, including peer punishment. However, this result provokes a number of questions. If centralized sanctioning is so successful, then why do many highly authoritarian states suffer from low levels of cooperation? Why do states with high levels of public good provision tend to rely more on citizen-driven peer punishment? And what happens if centralized institutions can be circumvented by individual acts of bribery? Here, we consider how corruption influences the evolution of cooperation and punishment. Our model shows that the effectiveness of centralized punishment in promoting cooperation breaks down when some actors in the model are allowed to bribe centralized authorities. Counterintuitively, increasing the sanctioning power of the central institution makes things even worse, since this prevents peer punishers from playing a role in maintaining cooperation. As a result, a weaker centralized authority is actually more effective because it allows peer punishment to restore cooperation in the presence of corruption. Our results provide an evolutionary rationale for why public goods provision rarely flourishes in polities that rely only on strong centralized institutions. Instead, cooperation requires both decentralized and centralized enforcement. These results help to explain why citizen participation is a fundamental necessity for policing the commons.Comment: 24 pages, 7 figures (Press embargo in place until publication

    Improving Multi-agent Learners Using Less-Biased Value Estimators

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