In this paper we describe the results of a set of experiments in which we compared the learning performance of human and machine learning agents. The problem involved the learning of a concept description for deciding on the legality of positions within the chess endgame King and Rook against King. Various amounts of background knowledge were made available to each learning agent. We concluded ...

This note describes a possible solution to some endgames in chess with many pieces, when a complete retrograde database construction will fail because of the size of the problem and the time needed to build it up. The note shows how human knowledge, position-specific limitations and existing databases can be combined to prove a position to be won, drawn or lost, and providing the game theoretic...

Ken Thompson recently communicated some results mined from his set of 64 6-man endgame tables. These list some positions of interest, namely, mutual zugzwangs and those of maximum depth. The results have been analysed by the authors and found to be identical or compatible with the available or published findings of Karrer, Nalimov, Stiller and Wirth.

The polio eradication endgame aims to bring transmission of all polioviruses to a halt. To achieve this aim, it is essential to block viral replication in individuals via induction of a robust mucosal immune response. Although it has long been recognized that inactivated poliovirus vaccine (IPV) is incapable of inducing a strong mucosal response on its own, it has recently become clear that IPV...

The World Health Organization declared India among other 10 countries in South East Region - as 'polio-free' in 2014. Since then, the Government of India (GoI) has scaled up its initiatives against polio endgame which targets virus eradication and sequential withdrawal of type 2 virus from oral polio vaccine (OPV). However, prior to choosing the switch from trivalent OPV (t-OPV) to bivalent OPV...

A board position evaluator is a crucial component for strong computer play in many games such as checkers, chess, and Reversi. The board evaluator is typically trained using pre-existing game data, an approach which is generally non-optimal, especially in the early stages of a game. Instead, we propose a new method which relies on Minimax search to train a series of models backwards from the en...