The purpose of reinforcement learning system is to learn an optimal policy in general. However, in 2players games such as the othello game, it is important to acquire a penalty avoiding policy. In this paper, we are focused on formation of penalty avoiding policies based on the Penalty Avoiding Rational Policy Making algorithm [2]. In applying it to large-scale problems, we are confronted with ...

This article surveys three techniques for enhancing heuristic game-tree search pioneered in the author’s Othello program LOGISTELLO, which dominated the computer Othello scene for several years and won against the human World-champion 6–0 in 1997. First, a generalized linear evaluation model (GLEM) is described that combines conjunctions of Boolean features linearly. This approach allows an aut...

From early days in computing, making computers play games like chess and Othello with a high level of skill has been a challenging and, lately, rewarding task. As computing power becomes increasingly more powerful, more and more complex learning techniques are employed to allow computers to learn different tasks. Games, however, remain a challenging and exciting domain for testing new technique...

William Shakespeare's plays, women play a central role in moving the plot forward. These become catalysts for drama that unfolds, especially tragedies, where reactions of other characters depend on actions women. Desdemona from Othello and Lady Macbeth this their respective plays. Both similar roles even though personalities are vastly different. becomes an almost stereotypical woman once she m...

This paper studies the effect of varying the depth of look-ahead for heuristic search in temporal difference (TD) learning and game playing. The acquisition position evaluation functions for the game of Othello is studied. The paper provides important insights into the strengths and weaknesses of using different search depths during learning when 2-greedy exploration is applied. The main findin...

The article presents Shakespeare's Iago as Hell's master therapist. Illustrated with excerpts from the play, the reader is shown how with consummate psychological skills, Iago bends his victims to his will. Step by step he awakens Othello's jealousy, and makes use of the hero's basic insecurity on account of his blackness. Once Othello has determined to take revenge, Iago makes sure to prevent ...

Achieving superhuman playing level by AlphaGo corroborated the capabilities of convolutional neural architectures (CNNs) for capturing complex spatial patterns. This result was to a great extent due to several analogies between Go board states and 2D images CNNs have been designed for, in particular translational invariance and a relatively large board. In this paper, we verify whether CNN-base...