'artificial intelligence'

Ms Pac-Man is one of the most challenging test beds in game artificial intelligence (AI). Genetic programming and Monte Carlo Tree Search (MCTS) have already been successful applied to several games including Pac-Man. In this paper, we use Monte ...

Supply Chain Management (SCM) is a complex process which includes a number of interrelated activities such as: negotiating with suppliers for raw materials, competing for customer orders, managing inventory, scheduling production, and delivering ...

Multi-agent reinforcement learning for multi-robot systems is a challenging issue in both robotics and artificial intelligence. With the ever increasing interests in theoretical researches and practical applications, currently there have been a lot ...

Bill Joy in a widely read but controversial article claimed that the most powerful 21st century technologies are threatening to make humans an endangered species. Indeed, a growing number of scientists, philosophers and forecasters insist that the ...

Interest in the role of artificial intelligence in interactive systems has grown rapidly in recent years, in part because increasingly powerful consumer hardware makes research-level AI usable in real-world games and/or immersive learning ...

Motivated by privacy and security concerns in online social networks, we study the role of social pressure in opinion games. These are games, important in economics and sociology, that model the formation of opinions in a social network. We enrich ...

The majority of existing artificial intelligence (AI) studies in computational finance literature are devoted solely to predicting market movements. In this paper we shift the attention to how AI can be applied to control risk-based money management ...

<jats:p>In this paper we describe a new method for EEG signal classification in which the classification of one subject’s EEG signals is based on features learnt from another subject. This method applies to the power spectrum density data and ...

Public sector organisations are increasingly interested in using data science and artificial intelligence capabilities to deliver policy and generate efficiencies in high uncertainty environments. The long-term success of data science and AI in the ...

Fuelled by successes in Computer Go, Monte Carlo tree search (MCTS) has achieved widespread adoption within the games community. Its links to traditional reinforcement learning (RL) methods have been outlined in the past; however, the use of RL ...