In deep reinforcement learning, searching and learning techniques are two important components. They can be used independently and in combination to deal with different problems in AI. These... Show moreIn deep reinforcement learning, searching and learning techniques are two important components. They can be used independently and in combination to deal with different problems in AI. These results have inspired research into artificial general intelligence (AGI).We study table based classic Q-learning on the General Game Playing (GGP) system, showing that classic Q-learning works on GGP, although convergence is slow, and it is computationally expensive to learn complex games.This dissertation uses an AlphaZero-like self-play framework to explore AGI on small games. By tuning different hyper-parameters, the role, effects and contributions of searching and learning are studied. A further experiment shows that search techniques can contribute as experts to generate better training examples to speed up the start phase of training.In order to extend the AlphaZero-likeself-play approach to single player complex games, the Morpion Solitaire game is implemented by combining Ranked Reward method. Our first AlphaZero-based approach is able to achieve a near human best record.Overall, in this thesis, both searching and learning techniques are studied (by themselves and in combination) in GGP and AlphaZero-like self-play systems. We do so for the purpose of making steps towards artificial general intelligence, towards systems that exhibit intelligent behavior in more than one domain. Show less
Continuous optimization is never easy: the exact solution is always a luxury demand and the theory of it is not always analytical and elegant. Continuous optimization, in practice, is... Show moreContinuous optimization is never easy: the exact solution is always a luxury demand and the theory of it is not always analytical and elegant. Continuous optimization, in practice, is essentially about the efficiency: how to obtain the solution with same quality using as minimal resources (e.g., CPU time or memory usage) as possible? In this thesis, the number of function evaluations is considered as the most important resource to save. To achieve this goal, various efforts have been implemented and applied successfully. One research stream focuses on the so-called stochastic variation (mutation) operator, which conducts an (local) exploration of the search space. The efficiency of those operator has been investigated closely, which shows a good stochastic variation should be able to generate a good coverage of the local neighbourhood around the current search solution. This thesis contributes on this issue by formulating a novel stochastic variation that yields good space coverage. Show less
English has become the language of international communication. As a result of this development, we are now confronted with a bewildering variety of ‘Englishes’, spoken with non-native accents.... Show moreEnglish has become the language of international communication. As a result of this development, we are now confronted with a bewildering variety of ‘Englishes’, spoken with non-native accents. Research determining how intelligible non-native speakers of varying native-language backgrounds are to each other and to native speakers of English has only just started to receive attention. This thesis investigated to what extent Chinese, Dutch and American speakers of English are mutually intelligible. Intelligibility of vowels, simplex consonants and consonant clusters was tested in meaningless sound sequences, as well as in words in meaningless and meaningful short sentences. Speakers (one male, one female per language background) were selected so as to be optimally representative of their peer groups, which were made up of young academic users of English. Intelligibility was tested for all nine combinations of speaker and listener backgrounds. Results show that Chinese-accented English is less intelligible overall than Dutch-accented English, which is less intelligible than American English. Generally, the native-language background of the speaker was less important for the intelligibility than the background of the listener. Also, the results reveal a clear and consistent so-called interlanguage speech intelligibility benefit: speakers of English – whether foreign or native – are more intelligible to listeners with whom they share the native-language background than to listeners with a different native language. Show less
