Manifesto of the Fourth International to the workers and peasants of India

https://stars.library.ucf.edu/prism/1579/thumbnail.jp

The death agony of capitalism and the tasks of the Fourth International: The transitional program adopted by the Founding Conference of the Fourth International

https://stars.library.ucf.edu/prism/1072/thumbnail.jp

Manifesto of the Fourth International on the imperialist war and the proletarian revolution

https://stars.library.ucf.edu/prism/1273/thumbnail.jp

Only victorious socialist revolutions can prevent the third world war!: Manifesto of the Fourth International to the workers, the exploited and the oppressed colonial peoples of the entire world.

https://stars.library.ucf.edu/prism/1375/thumbnail.jp

Analysing the relevance of experience partitions to the prediction of players’ self-reports of affect

A common practice in modeling affect from physiological signals consists of reducing the signals to a set of statistical features that feed predictors of self-reported emotions. This paper analyses the impact of various time-windows, used for the extraction of physiological features, to the accuracy of affective models of players in a simple 3D game. Results show that the signals recorded in the central part of a short gaming experience contain more relevant information to the prediction of positive affective states than the starting and ending parts while the relevant information to predict anxiety and frustration appear not to be localized in a specific time interval but rather dependent on particular game stimuli.peer-reviewe

Building a semantically transparent corpus for the generation of referring expressions

This paper discusses the construction of a corpus for the evaluation of algorithms that generate referring expressions. It is argued that such an evaluation task requires a semantically transparent corpus, and controlled experiments are the best way to create such a resource. We address a number of issues that have arisen in an ongoing evaluation study, among which is the problem of judging the output of GRE algorithms against a human gold standard.peer-reviewe

Transforming exploratory creativity with DeLeNoX

We introduce DeLeNoX (Deep Learning Novelty Explorer), a system that autonomously creates artifacts in constrained spaces according to its own evolving interestingness criterion. DeLeNoX proceeds in alternating phases of exploration and transformation. In the exploration phases, a version of novelty search augmented with constraint handling searches for maximally diverse artifacts using a given distance function. In the transformation phases, a deep learning autoencoder learns to compress the variation between the found artifacts into a lower-dimensional space. The newly trained encoder is then used as the basis for a new distance function, transforming the criteria for the next exploration phase. In the current paper, we apply DeLeNoX to the creation of spaceships suitable for use in two-dimensional arcade-style computer games, a representative problem in procedural content generation in games. We also situate DeLeNoX in relation to the distinction between exploratory and transformational creativity, and in relation to Schmidhuber’s theory of creativity through the drive for compression progress.peer-reviewe

Static and dynamic analysis for robustness under slowdown

Robustness of embedded systems to potential changes in their environment, which may result in the inputs being affected, is crucial for reliable behaviour. One typical possible change is that the system’s inputs are slowed down, altering its temporal behaviour. Algorithmic analysis of systems to be able to deduce their robustness under such environmental interference is desirable. In this paper, we present a framework for the analysis of synchronous systems to analyse their behaviour when the inputs slow down through stuttering. We identify different types of slowdown robustness constraints and present static and dynamic analysis techniques for determining whether systems written in Lustre satisfy these robustness properties.peer-reviewe

Temporal planning with semantic attachment of non-linear monotonic continuous behaviour

Non-linear continuous change is common in realworld problems, especially those that model physical systems. We present an algorithm which builds upon existent temporal planning techniques based on linear programming to approximate non-linear continuous monotonic functions. These are integrated through a semantic attachment mechanism, allowing external libraries or functions that are difficult to model in native PDDL to be evaluated during the planning process. A new planning system implementing this algorithm was developed and evaluated. Results show that the addition of this algorithm to the planning process can enable it to solve a broader set of planning problems.peer-reviewe