Procedural Content Generation is now used in many games to generate a wide variety of content. It often uses players controlled by Artificial Intelligence for its evaluation. PCG content can also be used when training AI players to achieve better generalization. In both of these fields, evolutionary algorithms are employed, but they are rarely used together. In this thesis, we use the coevolution of AI players and level generators for platformer game Super Mario. Coevolution's benefit is, that the AI players are evaluated by adapting level generators, and vice versa, level generators are evaluated by adapting AI players. This approach has two results. The first one is a creation of multiple level generators, each generating levels of gradually increased difficulty. Levels generated using a sequence of these generators also mirror the learning curve of the AI player. This can be useful also for human players playing the game for the first time. The second result is an AI player, which was evolved on gradually more difficult levels. Making it learn progressively may yield better results. Using the coevolution also doesn't require any training data set.

Chalcid wasps (Chalciodiodea) is superfamily within parasitic group of the order Hymenoptera. These insects attack other arthropods. My thesis is focused on phylogeny of selected species groups of the genus Torymus Dalman 1820, whose range of hosts includes mainly gall-forming insect as gall wasps (Hymenoptera: Cynipidae) and gall midges (Diptera: Cecidomyiidae). Using genes 28D2 rDNA, COI and CytB, I constructed phylogenetic trees, which helped with discussing current view on classification of the genus and with inferring new findings about co-evolution with host organisms. Previously established morphological - ecological species groups were not supported by my analyses in many cases. Morphological traits seem to be convergent for many species. They often do not support observed monophyla as apomorphies. On the other hand, ecology and natural habitat of species was common for many branches in my cladograms. It was found out, that recent hosts are not probably original hosts of the group. Adaptive radiation in different habitats is likely to be the phenomenon that stands behind present-day host range of Torymus species. This process could have occurred after swapping to gall midges and gall wasps. Key words: Chalcidoidea, Torymus, phylogeny, parasitoid, host specifity, co-evolution

The goal of this work is to present attitudes of two contemporary authors who are in the center of the evolutionary-origin-of morality debate, that is theories of Richard Dawkins and Frans de Waal. The critical reflection of their works on this topic will center around the building blocks of morality and the supposed "moral sense", which according to the dutch primatologist humans to some extent share with some of their living evolutinary relatives. In case of Richard Dawkins we are about to review his meme theory and parasytical character of some elements of culture. Morevoer there will be presented accounts of the dual inheritance theorists, which in authors opinion can reunite both presented authors and thier attitudes, i.e. put the parasytic/independent character of memes in accordance with the building blocks of morality approach. This approach in turn can explain many phenomena of human contemporary morals and their limits. Keywords: Morality, evolution, dual inheritance theory, coevolution, memes

Sustainable strategic management emerged from the coevolution of strategic thinking in today's sustainability challenging business environment. Business ecosystems, designed to create socially and ecologically responsible economic opportunities for their members, have emerged as excellent structures for implementing sustainable strategic management strategies along the whole pyramid of coevolving developed, developing, and undeveloped markets. Both the business ecosystem leaders and niche players in these whole pyramid business ecosystems have critical roles to play in formulating and implementing potentially profitable strategies that help reduce the human footprint and improve the quality of human life. Ecosystem leaders need to be responsible for creating and shepherding their business ecosystems' visions of a sustainable future, and niche players need to be responsible for providing the ecosystem with an innovation trajectory designed to make those visions a reality.

Sustainable strategic management emerged from the coevolution of strategic thinking in today's sustainability challenging business environment. Business ecosystems, designed to create socially and ecologically responsible economic opportunities for their members, have emerged as excellent structures for implementing sustainable strategic management strategies along the whole pyramid of coevolving developed, developing, and undeveloped markets. Both the business ecosystem leaders and niche players in these whole pyramid business ecosystems have critical roles to play in formulating and implementing potentially profitable strategies that help reduce the human footprint and improve the quality of human life. Ecosystem leaders need to be responsible for creating and shepherding their business ecosystems' visions of a sustainable future, and niche players need to be responsible for providing the ecosystem with an innovation trajectory designed to make those visions a reality.

This thesis investigates the use of Bayesian analysis upon an opponent¿s behaviour in order to determine the desired goals or strategy used by a given adversary. A terrain analysis approach utilising the A* algorithm is investigated, where a probability distribution between discrete behaviours of an opponent relative to a set of possible goals is generated. The Bayesian analysis of agent behaviour accurately determines the intended goal of an opponent agent, even when the opponent¿s actions are altered randomly. The environment of Poker is introduced and abstracted for ease of analysis. Bayes¿ theorem is used to generate an effective opponent model, categorizing behaviour according to its similarity with known styles of opponent. The accuracy of Bayes¿ rule yields a notable improvement in the performance of an agent once an opponent¿s style is understood. A hybrid of the Bayesian style predictor and a neuroevolutionary approach is shown to lead to effective dynamic play, in comparison to agents that do not use an opponent model. The use of recurrence in evolved networks is also shown to improve the performance and generalizability of an agent in a multiplayer environment. These strategies are then employed in the full-scale environment of Texas Hold¿em, where a betting round-based approach proves useful in determining and counteracting an opponent¿s play. It is shown that the use of opponent models, with the adaptive benefits of neuroevolution aid the performance of an agent, even when the behaviour of an opponent does not necessarily fit within the strict definitions of opponent ¿style¿. / Engineering and Physical Sciences Research Council (EPSRC)

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