Abstract-Puzzles and board games represent several important classes of AI problems, but also represent difficult complexity classes. In this paper, we propose a deep learning based alternative to train a neural network model to find solution states of the popular puzzle game Sokoban. The network trains against a classical solver that uses theorem proving as the oracle of valid and invalid games states, in a setup that is similar to the popular adversarial training framework. Using our approach, we have been able to verify the validity of a Sokoban puzzle up to an accuracy of 99% on the test set. We have also been able to train our network to generate the next possible state of the puzzle board up to an accuracy of 99% on the validation set. We hope that through this approach, a trained neural network will be able to replace human experts and classical rule-based AI in generating new instances and solutions for such games.
Declared a pandemic in March 2020, SARS-COVID19 has become a health emergency of global concern. The World Health Organization has directed the countries all over the world to take measures to stop the spread of disease. There was a public outburst for policies like lockdown and a mixed review for Working from Home on social networking platforms. By analyzing this change, we can identify the sentiment of people about different policies. A lot of work has been done on sentiment analysis of Covid19 tweets. This is an in-depth impact analysis of COVID-19 response measures on sentiments of tweets. It can help us understand the social media trends revolving around COVID19. For achieving the goal, Google Mobility Report has been used for obtaining data about the mobility in different countries. A huge collection of tweets is extracted using Twitter API. Both datasets are used to analyze multiple trends over a period of more than a year. This article shows the change in social media sentiments with the evolving state of pandemic and the steps taken by authorities. Although, number of cases have more impact on Sentiments, the impact of changing mobility of residential and non-residential areas is also not negligible because average sentiments have seen significant up and down trends because of changing government policies.
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